初始化项目，由ModelHub XC社区提供模型
Model: hard007ik/shopmanager-grpo-qwen3 Source: Original Platform
This commit is contained in:
ModelHub XC
36
.gitattributes
vendored
Normal file
36
.gitattributes
vendored
Normal file
@@ -0,0 +1,36 @@
|
|||||||
|
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ftz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.gz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.h5 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.joblib filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.model filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.onnx filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ot filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.parquet filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pb filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||||
|
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tflite filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tgz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
||||||
69
README.md
Normal file
69
README.md
Normal file
@@ -0,0 +1,69 @@
|
|||||||
|
---
|
||||||
|
base_model: Qwen/Qwen3-1.7B
|
||||||
|
library_name: transformers
|
||||||
|
model_name: shopmanager-grpo-qwen3
|
||||||
|
tags:
|
||||||
|
- generated_from_trainer
|
||||||
|
- trackio:https://hard007ik-trackio.hf.space?project=huggingface&runs=hard007ik-1777188018&sidebar=collapsed
|
||||||
|
- hf_jobs
|
||||||
|
- grpo
|
||||||
|
- trl
|
||||||
|
licence: license
|
||||||
|
---
|
||||||
|
|
||||||
|
# Model Card for shopmanager-grpo-qwen3
|
||||||
|
|
||||||
|
This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B).
|
||||||
|
It has been trained using [TRL](https://github.com/huggingface/trl).
|
||||||
|
|
||||||
|
## Quick start
|
||||||
|
|
||||||
|
```python
|
||||||
|
from transformers import pipeline
|
||||||
|
|
||||||
|
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
|
||||||
|
generator = pipeline("text-generation", model="hard007ik/shopmanager-grpo-qwen3", device="cuda")
|
||||||
|
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
|
||||||
|
print(output["generated_text"])
|
||||||
|
```
|
||||||
|
|
||||||
|
## Training procedure
|
||||||
|
|
||||||
|
|
||||||
|
[<img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" width="150" height="24"/>](https://hard007ik-trackio.hf.space?project=huggingface&runs=hard007ik-1777188018&sidebar=collapsed)
|
||||||
|
|
||||||
|
|
||||||
|
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
|
||||||
|
|
||||||
|
### Framework versions
|
||||||
|
|
||||||
|
- TRL: 1.2.0
|
||||||
|
- Transformers: 4.57.6
|
||||||
|
- Pytorch: 2.10.0
|
||||||
|
- Datasets: 4.8.4
|
||||||
|
- Tokenizers: 0.22.2
|
||||||
|
|
||||||
|
## Citations
|
||||||
|
|
||||||
|
Cite GRPO as:
|
||||||
|
|
||||||
|
```bibtex
|
||||||
|
@article{shao2024deepseekmath,
|
||||||
|
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
|
||||||
|
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
|
||||||
|
year = 2024,
|
||||||
|
eprint = {arXiv:2402.03300},
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
Cite TRL as:
|
||||||
|
|
||||||
|
```bibtex
|
||||||
|
@software{vonwerra2020trl,
|
||||||
|
title = {{TRL: Transformers Reinforcement Learning}},
|
||||||
|
author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
|
||||||
|
license = {Apache-2.0},
|
||||||
|
url = {https://github.com/huggingface/trl},
|
||||||
|
year = {2020}
|
||||||
|
}
|
||||||
|
```
|
||||||
28
added_tokens.json
Normal file
28
added_tokens.json
Normal file
@@ -0,0 +1,28 @@
|
|||||||
|
{
|
||||||
|
"</think>": 151668,
|
||||||
|
"</tool_call>": 151658,
|
||||||
|
"</tool_response>": 151666,
|
||||||
|
"<think>": 151667,
|
||||||
|
"<tool_call>": 151657,
|
||||||
|
"<tool_response>": 151665,
|
||||||
|
"<|box_end|>": 151649,
|
||||||
|
"<|box_start|>": 151648,
|
||||||
|
"<|endoftext|>": 151643,
|
||||||
|
"<|file_sep|>": 151664,
|
||||||
|
"<|fim_middle|>": 151660,
|
||||||
|
"<|fim_pad|>": 151662,
|
||||||
|
"<|fim_prefix|>": 151659,
|
||||||
|
"<|fim_suffix|>": 151661,
|
||||||
|
"<|im_end|>": 151645,
|
||||||
|
"<|im_start|>": 151644,
|
||||||
|
"<|image_pad|>": 151655,
|
||||||
|
"<|object_ref_end|>": 151647,
|
||||||
|
"<|object_ref_start|>": 151646,
|
||||||
|
"<|quad_end|>": 151651,
|
||||||
|
"<|quad_start|>": 151650,
|
||||||
|
"<|repo_name|>": 151663,
|
||||||
|
"<|video_pad|>": 151656,
|
||||||
|
"<|vision_end|>": 151653,
|
||||||
|
"<|vision_pad|>": 151654,
|
||||||
|
"<|vision_start|>": 151652
|
||||||
|
}
|
||||||
89
chat_template.jinja
Normal file
89
chat_template.jinja
Normal file
@@ -0,0 +1,89 @@
|
|||||||
|
{%- if tools %}
|
||||||
|
{{- '<|im_start|>system\n' }}
|
||||||
|
{%- if messages[0].role == 'system' %}
|
||||||
|
{{- messages[0].content + '\n\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||||
|
{%- for tool in tools %}
|
||||||
|
{{- "\n" }}
|
||||||
|
{{- tool | tojson }}
|
||||||
|
{%- endfor %}
|
||||||
|
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||||
|
{%- else %}
|
||||||
|
{%- if messages[0].role == 'system' %}
|
||||||
|
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||||
|
{%- for message in messages[::-1] %}
|
||||||
|
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||||
|
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||||
|
{%- set ns.multi_step_tool = false %}
|
||||||
|
{%- set ns.last_query_index = index %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- for message in messages %}
|
||||||
|
{%- if message.content is string %}
|
||||||
|
{%- set content = message.content %}
|
||||||
|
{%- else %}
|
||||||
|
{%- set content = '' %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||||
|
{%- elif message.role == "assistant" %}
|
||||||
|
{%- set reasoning_content = '' %}
|
||||||
|
{%- if message.reasoning_content is string %}
|
||||||
|
{%- set reasoning_content = message.reasoning_content %}
|
||||||
|
{%- else %}
|
||||||
|
{%- if '</think>' in content %}
|
||||||
|
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||||
|
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if loop.index0 > ns.last_query_index %}
|
||||||
|
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||||
|
{%- else %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- else %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if message.tool_calls %}
|
||||||
|
{%- for tool_call in message.tool_calls %}
|
||||||
|
{%- if (loop.first and content) or (not loop.first) %}
|
||||||
|
{{- '\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if tool_call.function %}
|
||||||
|
{%- set tool_call = tool_call.function %}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '<tool_call>\n{"name": "' }}
|
||||||
|
{{- tool_call.name }}
|
||||||
|
{{- '", "arguments": ' }}
|
||||||
|
{%- if tool_call.arguments is string %}
|
||||||
|
{{- tool_call.arguments }}
|
||||||
|
{%- else %}
|
||||||
|
{{- tool_call.arguments | tojson }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '}\n</tool_call>' }}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- elif message.role == "tool" %}
|
||||||
|
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||||
|
{{- '<|im_start|>user' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '\n<tool_response>\n' }}
|
||||||
|
{{- content }}
|
||||||
|
{{- '\n</tool_response>' }}
|
||||||
|
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- if add_generation_prompt %}
|
||||||
|
{{- '<|im_start|>assistant\n' }}
|
||||||
|
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||||
|
{{- '<think>\n\n</think>\n\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
60
config.json
Normal file
60
config.json
Normal file
@@ -0,0 +1,60 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"Qwen3ForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_bias": false,
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"dtype": "float32",
|
||||||
|
"eos_token_id": 151645,
|
||||||
|
"head_dim": 128,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2048,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 6144,
|
||||||
|
"layer_types": [
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention"
|
||||||
|
],
|
||||||
|
"max_position_embeddings": 40960,
|
||||||
|
"max_window_layers": 28,
|
||||||
|
"model_type": "qwen3",
|
||||||
|
"num_attention_heads": 16,
|
||||||
|
"num_hidden_layers": 28,
|
||||||
|
"num_key_value_heads": 8,
|
||||||
|
"pad_token_id": 151643,
|
||||||
|
"rms_norm_eps": 1e-06,
|
||||||
|
"rope_scaling": null,
|
||||||
|
"rope_theta": 1000000,
|
||||||
|
"sliding_window": null,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"transformers_version": "4.57.6",
|
||||||
|
"use_cache": true,
|
||||||
|
"use_sliding_window": false,
|
||||||
|
"vocab_size": 151936
|
||||||
|
}
|
||||||
12
generation_config.json
Normal file
12
generation_config.json
Normal file
@@ -0,0 +1,12 @@
|
|||||||
|
{
|
||||||
|
"do_sample": true,
|
||||||
|
"eos_token_id": [
|
||||||
|
151645,
|
||||||
|
151643
|
||||||
|
],
|
||||||
|
"pad_token_id": 151643,
|
||||||
|
"temperature": 0.6,
|
||||||
|
"top_k": 20,
|
||||||
|
"top_p": 0.95,
|
||||||
|
"transformers_version": "4.57.6"
|
||||||
|
}
|
||||||
BIN
loss_curve.png
Normal file
BIN
loss_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 40 KiB |
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
20
metrics.csv
Normal file
20
metrics.csv
Normal file
@@ -0,0 +1,20 @@
|
|||||||
|
step,loss,grad_norm,learning_rate,num_tokens,completions/mean_length,completions/min_length,completions/max_length,completions/clipped_ratio,completions/mean_terminated_length,completions/min_terminated_length,completions/max_terminated_length,rewards/reward_total/mean,rewards/reward_total/std,rewards/reward_market/mean,rewards/reward_market/std,rewards/reward_warehouse/mean,rewards/reward_warehouse/std,rewards/reward_showroom/mean,rewards/reward_showroom/std,reward,reward_std,frac_reward_zero_std,sampling/sampling_logp_difference/mean,sampling/sampling_logp_difference/max,sampling/importance_sampling_ratio/min,sampling/importance_sampling_ratio/mean,sampling/importance_sampling_ratio/max,entropy,clip_ratio/low_mean,clip_ratio/low_min,clip_ratio/high_mean,clip_ratio/high_max,clip_ratio/region_mean,step_time,epoch,train_runtime,train_samples_per_second,train_steps_per_second,total_flos,train_loss
|
||||||
|
1,-0.009,12.235088348388672,0.0,27758.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7793656587600708,0.12745577096939087,0.25,0.13440430164337158,0.42500001192092896,0.20160645246505737,0.10436563193798065,0.069697305560112,0.7793656587600708,0.12745577096939087,0.0,0.005470390431582928,0.22214925289154053,0.8007970452308655,0.9949374794960022,1.076386570930481,0.028439456821217846,0.0,0.0,0.0,0.0,0.0,19.228480510413647,0.05555555555555555,,,,,
|
||||||
|
2,0.0723,60.551937103271484,5.000000000000001e-07,55324.0,3.25,3.0,7.0,0.0,3.25,3.0,7.0,0.719434380531311,0.1505809724330902,0.30000001192092896,0.17597654461860657,0.30000001192092896,0.17597654461860657,0.11943437159061432,0.07055392116308212,0.719434380531311,0.1505809724330902,0.0,0.01085888221859932,0.28092825412750244,0.8382877111434937,1.0260276794433594,1.324359655380249,0.036137547835437545,0.0,0.0,0.0,0.0,0.0,17.92062332853675,0.1111111111111111,,,,,
|
||||||
|
3,0.1153,232.934814453125,1.0000000000000002e-06,83000.0,3.5,3.0,7.0,0.0,3.5,3.0,7.0,0.7885687351226807,0.1279384195804596,0.32500001788139343,0.18837162852287292,0.375,0.20160646736621857,0.08856874704360962,0.07010025531053543,0.7885687351226807,0.1279384344816208,0.0,0.0251829382032156,0.6850378513336182,0.5226751565933228,1.0358223915100098,1.9838452339172363,0.03248842835137111,0.0,0.0,0.0,0.0,0.0,17.184778176248074,0.16666666666666666,,,,,
|
||||||
|
4,0.0243,13.620709419250488,1.5e-06,110708.0,3.125,3.0,7.0,0.0,3.125,3.0,7.0,0.7762374877929688,0.13016164302825928,0.32499998807907104,0.18837164342403412,0.3500000238418579,0.1967477649450302,0.10123749077320099,0.06825561076402664,0.7762374877929688,0.13016162812709808,0.0,0.007013080175966024,0.2646750509738922,0.7674550414085388,0.9837819337844849,1.0260045528411865,0.03743034108288157,0.0,0.0,0.0,0.0,0.0,17.90316915512085,0.2222222222222222,,,,,
|
||||||
|
5,0.0004,2.0591225624084473,2.0000000000000003e-06,138452.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7784374952316284,0.12858590483665466,0.30000001192092896,0.17597654461860657,0.375,0.20160646736621857,0.10343749821186066,0.06380020827054977,0.7784374952316284,0.12858593463897705,0.0,0.001465568202547729,0.05673474818468094,0.9749767780303955,1.0017430782318115,1.058376669883728,0.008188390799773515,0.0,0.0,0.0,0.0,0.0,17.8210555203259,0.2777777777777778,,,,,
|
||||||
|
6,0.0915,31.611696243286133,2.5e-06,166252.0,3.125,3.0,7.0,0.0,3.125,3.0,7.0,0.7915937900543213,0.12960509955883026,0.375,0.20160646736621857,0.32500001788139343,0.18837162852287292,0.09159374982118607,0.0639258474111557,0.7915937900543213,0.12960509955883026,0.0,0.008641102351248264,0.8236088752746582,0.9935171008110046,1.0399717092514038,2.278707504272461,0.007084679029730978,0.0,0.0,0.0,0.0,0.0,18.056264080107212,0.3333333333333333,,,,,
|
||||||
|
7,-0.0,0.281630277633667,3e-06,193950.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7600874900817871,0.13816162943840027,0.32500001788139343,0.18837162852287292,0.32500001788139343,0.18837162852287292,0.11008749902248383,0.07028691470623016,0.7600874900817871,0.13816164433956146,0.0,3.554227441782132e-05,0.0027569520752876997,0.997247576713562,0.9999052286148071,1.0000724792480469,0.0005298306713825696,0.0,0.0,0.0,0.0,0.0,17.43799263238907,0.3888888888888889,,,,,
|
||||||
|
8,0.0,0.00018881642608903348,3.5e-06,221677.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7622687816619873,0.1372590959072113,0.4000000059604645,0.20320022106170654,0.25,0.13440430164337158,0.11226874589920044,0.07360353320837021,0.7622687816619873,0.1372590959072113,0.0,2.545601773817907e-07,1.5496943888138048e-06,0.9999986886978149,1.000000238418579,1.0000016689300537,4.1391018498870835e-05,0.0,0.0,0.0,0.0,0.0,17.406394600868225,0.4444444444444444,,,,,
|
||||||
|
9,0.0,0.00015632262511644512,4.000000000000001e-06,249549.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.775946855545044,0.137176051735878,0.375,0.20160646736621857,0.30000001192092896,0.17597654461860657,0.10094687342643738,0.058497413992881775,0.775946855545044,0.1371760368347168,0.0,2.918131087881193e-07,3.099441755693988e-06,0.9999978542327881,1.0,1.000001311302185,4.173239403826301e-05,0.0,0.0,0.0,0.0,0.0,18.514019537717104,0.5,,,,,
|
||||||
|
10,0.0,9.833038348006085e-05,4.5e-06,277377.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7337374687194824,0.15055809915065765,0.2750000059604645,0.1586231142282486,0.3500000238418579,0.1967477649450302,0.10873749852180481,0.06778524816036224,0.7337374687194824,0.15055811405181885,0.0,2.719489771152439e-07,1.9073031580774114e-06,0.9999985694885254,0.9999998807907104,1.0000019073486328,4.224909940830912e-05,0.0,0.0,0.0,0.0,0.0,18.26371632888913,0.5555555555555556,,,,,
|
||||||
|
11,-0.0,0.00015879125567153096,5e-06,305332.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7567968368530273,0.13728150725364685,0.375,0.20160646736621857,0.2750000059604645,0.1586231142282486,0.10679687559604645,0.07404065877199173,0.7567968368530273,0.13728150725364685,0.0,3.067227396513772e-07,2.6226434783893637e-06,0.9999973773956299,0.9999994039535522,1.0000019073486328,4.7876037001515215e-05,0.0,0.0,0.0,0.0,0.0,19.4472255371511,0.6111111111111112,,,,,
|
||||||
|
12,-0.0,0.00039661259506829083,4.3750000000000005e-06,333165.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7081500291824341,0.1421954482793808,0.30000001192092896,0.17597654461860657,0.2750000059604645,0.1586231142282486,0.13315001130104065,0.07370516657829285,0.7081500291824341,0.142195463180542,0.0,4.768499479723687e-07,5.602954843197949e-06,0.9999943971633911,0.9999988675117493,1.0000016689300537,5.9777358274004655e-05,0.0,0.0,0.0,0.0,0.0,18.45015063509345,0.6666666666666666,,,,,
|
||||||
|
13,0.0,0.0005282312049530447,3.7500000000000005e-06,361006.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7762781381607056,0.13823458552360535,0.32500001788139343,0.18837162852287292,0.3500000238418579,0.1967477649450302,0.10127812623977661,0.06158862262964249,0.7762781381607056,0.13823460042476654,0.0,6.830008487668238e-07,5.60290391149465e-06,0.9999943971633911,0.9999983310699463,1.0000022649765015,7.182803437899565e-05,0.0,0.0,0.0,0.0,0.0,17.955969959497452,0.7222222222222222,,,,,
|
||||||
|
14,-0.0,0.000535853614564985,3.125e-06,388862.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7628874778747559,0.1295449286699295,0.30000001192092896,0.17597654461860657,0.3499999940395355,0.19674775004386902,0.11288750171661377,0.073255755007267,0.7628874778747559,0.1295449435710907,0.0,1.1113726259281975e-06,2.0979605324100703e-05,0.9999922513961792,1.0000004768371582,1.0000211000442505,9.972968496185786e-05,0.0,0.0,0.0,0.0,0.0,18.99697282537818,0.7777777777777778,,,,,
|
||||||
|
15,0.0,0.005312301218509674,2.5e-06,416636.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7899656295776367,0.1296130269765854,0.3499999940395355,0.19674775004386902,0.3500000238418579,0.1967477649450302,0.08996562659740448,0.05463240668177605,0.7899656295776367,0.12961304187774658,0.0,4.004845322924666e-06,4.589592936099507e-05,0.9999337792396545,0.9999885559082031,1.0000029802322388,0.0001807671503684105,0.0,0.0,0.0,0.0,0.0,19.184648096561432,0.8333333333333334,,,,,
|
||||||
|
16,-0.0,0.005995223298668861,1.8750000000000003e-06,444544.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.789996862411499,0.12048782408237457,0.375,0.20160646736621857,0.32039374113082886,0.18316024541854858,0.09460312128067017,0.062435995787382126,0.789996862411499,0.12048781663179398,0.0,4.866625204158481e-06,2.9087463190080598e-05,0.999959409236908,0.9999855160713196,1.0000004768371582,0.00019320984370096994,0.0,0.0,0.0,0.0,0.0,19.476148523390293,0.8888888888888888,,,,,
|
||||||
|
17,0.0,0.011378168128430843,1.25e-06,472481.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.8168656826019287,0.09262391924858093,0.375,0.20160646736621857,0.3498094081878662,0.19690066576004028,0.09205625206232071,0.07046373933553696,0.8168656826019287,0.09262390434741974,0.0,5.950785180175444e-06,4.7328881919384e-05,0.9999284744262695,0.9999822974205017,1.000001072883606,0.00021975090658088448,0.0,0.0,0.0,0.0,0.0,19.344543006271124,0.9444444444444444,,,,,
|
||||||
|
18,0.0,0.018683306872844696,6.25e-07,500266.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7750625014305115,0.14084643125534058,0.3500000238418579,0.1967477649450302,0.32499998807907104,0.18837164342403412,0.10006250441074371,0.05640558898448944,0.7750625014305115,0.14084644615650177,0.0625,1.1303089195280336e-05,0.00027322862297296524,0.999584436416626,0.9999662637710571,0.9999997615814209,0.000320568448614722,0.0,0.0,0.0,0.0,0.0,17.66909484937787,1.0,,,,,
|
||||||
|
18,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1.0,406.352,0.738,0.044,0.0,0.016376476217475202
|
||||||
|
695
metrics.json
Normal file
695
metrics.json
Normal file
@@ -0,0 +1,695 @@
|
|||||||
|
[
|
||||||
|
{
|
||||||
|
"step": 1,
|
||||||
|
"loss": -0.009,
|
||||||
|
"grad_norm": 12.235088348388672,
|
||||||
|
"learning_rate": 0.0,
|
||||||
|
"num_tokens": 27758.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7793656587600708,
|
||||||
|
"rewards/reward_total/std": 0.12745577096939087,
|
||||||
|
"rewards/reward_market/mean": 0.25,
|
||||||
|
"rewards/reward_market/std": 0.13440430164337158,
|
||||||
|
"rewards/reward_warehouse/mean": 0.42500001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160645246505737,
|
||||||
|
"rewards/reward_showroom/mean": 0.10436563193798065,
|
||||||
|
"rewards/reward_showroom/std": 0.069697305560112,
|
||||||
|
"reward": 0.7793656587600708,
|
||||||
|
"reward_std": 0.12745577096939087,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.005470390431582928,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.22214925289154053,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.8007970452308655,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9949374794960022,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.076386570930481,
|
||||||
|
"entropy": 0.028439456821217846,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.228480510413647,
|
||||||
|
"epoch": 0.05555555555555555
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 2,
|
||||||
|
"loss": 0.0723,
|
||||||
|
"grad_norm": 60.551937103271484,
|
||||||
|
"learning_rate": 5.000000000000001e-07,
|
||||||
|
"num_tokens": 55324.0,
|
||||||
|
"completions/mean_length": 3.25,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.25,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.719434380531311,
|
||||||
|
"rewards/reward_total/std": 0.1505809724330902,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_showroom/mean": 0.11943437159061432,
|
||||||
|
"rewards/reward_showroom/std": 0.07055392116308212,
|
||||||
|
"reward": 0.719434380531311,
|
||||||
|
"reward_std": 0.1505809724330902,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.01085888221859932,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.28092825412750244,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.8382877111434937,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0260276794433594,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.324359655380249,
|
||||||
|
"entropy": 0.036137547835437545,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.92062332853675,
|
||||||
|
"epoch": 0.1111111111111111
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 3,
|
||||||
|
"loss": 0.1153,
|
||||||
|
"grad_norm": 232.934814453125,
|
||||||
|
"learning_rate": 1.0000000000000002e-06,
|
||||||
|
"num_tokens": 83000.0,
|
||||||
|
"completions/mean_length": 3.5,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.5,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7885687351226807,
|
||||||
|
"rewards/reward_total/std": 0.1279384195804596,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.375,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_showroom/mean": 0.08856874704360962,
|
||||||
|
"rewards/reward_showroom/std": 0.07010025531053543,
|
||||||
|
"reward": 0.7885687351226807,
|
||||||
|
"reward_std": 0.1279384344816208,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.0251829382032156,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.6850378513336182,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.5226751565933228,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0358223915100098,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.9838452339172363,
|
||||||
|
"entropy": 0.03248842835137111,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.184778176248074,
|
||||||
|
"epoch": 0.16666666666666666
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 4,
|
||||||
|
"loss": 0.0243,
|
||||||
|
"grad_norm": 13.620709419250488,
|
||||||
|
"learning_rate": 1.5e-06,
|
||||||
|
"num_tokens": 110708.0,
|
||||||
|
"completions/mean_length": 3.125,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.125,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7762374877929688,
|
||||||
|
"rewards/reward_total/std": 0.13016164302825928,
|
||||||
|
"rewards/reward_market/mean": 0.32499998807907104,
|
||||||
|
"rewards/reward_market/std": 0.18837164342403412,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10123749077320099,
|
||||||
|
"rewards/reward_showroom/std": 0.06825561076402664,
|
||||||
|
"reward": 0.7762374877929688,
|
||||||
|
"reward_std": 0.13016162812709808,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.007013080175966024,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.2646750509738922,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.7674550414085388,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9837819337844849,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0260045528411865,
|
||||||
|
"entropy": 0.03743034108288157,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.90316915512085,
|
||||||
|
"epoch": 0.2222222222222222
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 5,
|
||||||
|
"loss": 0.0004,
|
||||||
|
"grad_norm": 2.0591225624084473,
|
||||||
|
"learning_rate": 2.0000000000000003e-06,
|
||||||
|
"num_tokens": 138452.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7784374952316284,
|
||||||
|
"rewards/reward_total/std": 0.12858590483665466,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.375,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_showroom/mean": 0.10343749821186066,
|
||||||
|
"rewards/reward_showroom/std": 0.06380020827054977,
|
||||||
|
"reward": 0.7784374952316284,
|
||||||
|
"reward_std": 0.12858593463897705,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.001465568202547729,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.05673474818468094,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9749767780303955,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0017430782318115,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.058376669883728,
|
||||||
|
"entropy": 0.008188390799773515,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.8210555203259,
|
||||||
|
"epoch": 0.2777777777777778
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 6,
|
||||||
|
"loss": 0.0915,
|
||||||
|
"grad_norm": 31.611696243286133,
|
||||||
|
"learning_rate": 2.5e-06,
|
||||||
|
"num_tokens": 166252.0,
|
||||||
|
"completions/mean_length": 3.125,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.125,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7915937900543213,
|
||||||
|
"rewards/reward_total/std": 0.12960509955883026,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_showroom/mean": 0.09159374982118607,
|
||||||
|
"rewards/reward_showroom/std": 0.0639258474111557,
|
||||||
|
"reward": 0.7915937900543213,
|
||||||
|
"reward_std": 0.12960509955883026,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.008641102351248264,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.8236088752746582,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9935171008110046,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0399717092514038,
|
||||||
|
"sampling/importance_sampling_ratio/max": 2.278707504272461,
|
||||||
|
"entropy": 0.007084679029730978,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.056264080107212,
|
||||||
|
"epoch": 0.3333333333333333
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 7,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.281630277633667,
|
||||||
|
"learning_rate": 3e-06,
|
||||||
|
"num_tokens": 193950.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7600874900817871,
|
||||||
|
"rewards/reward_total/std": 0.13816162943840027,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_showroom/mean": 0.11008749902248383,
|
||||||
|
"rewards/reward_showroom/std": 0.07028691470623016,
|
||||||
|
"reward": 0.7600874900817871,
|
||||||
|
"reward_std": 0.13816164433956146,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 3.554227441782132e-05,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.0027569520752876997,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.997247576713562,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999052286148071,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000724792480469,
|
||||||
|
"entropy": 0.0005298306713825696,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.43799263238907,
|
||||||
|
"epoch": 0.3888888888888889
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 8,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.00018881642608903348,
|
||||||
|
"learning_rate": 3.5e-06,
|
||||||
|
"num_tokens": 221677.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7622687816619873,
|
||||||
|
"rewards/reward_total/std": 0.1372590959072113,
|
||||||
|
"rewards/reward_market/mean": 0.4000000059604645,
|
||||||
|
"rewards/reward_market/std": 0.20320022106170654,
|
||||||
|
"rewards/reward_warehouse/mean": 0.25,
|
||||||
|
"rewards/reward_warehouse/std": 0.13440430164337158,
|
||||||
|
"rewards/reward_showroom/mean": 0.11226874589920044,
|
||||||
|
"rewards/reward_showroom/std": 0.07360353320837021,
|
||||||
|
"reward": 0.7622687816619873,
|
||||||
|
"reward_std": 0.1372590959072113,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.545601773817907e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 1.5496943888138048e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999986886978149,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.000000238418579,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000016689300537,
|
||||||
|
"entropy": 4.1391018498870835e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.406394600868225,
|
||||||
|
"epoch": 0.4444444444444444
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 9,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.00015632262511644512,
|
||||||
|
"learning_rate": 4.000000000000001e-06,
|
||||||
|
"num_tokens": 249549.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.775946855545044,
|
||||||
|
"rewards/reward_total/std": 0.137176051735878,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_showroom/mean": 0.10094687342643738,
|
||||||
|
"rewards/reward_showroom/std": 0.058497413992881775,
|
||||||
|
"reward": 0.775946855545044,
|
||||||
|
"reward_std": 0.1371760368347168,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.918131087881193e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 3.099441755693988e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999978542327881,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.000001311302185,
|
||||||
|
"entropy": 4.173239403826301e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.514019537717104,
|
||||||
|
"epoch": 0.5
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 10,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 9.833038348006085e-05,
|
||||||
|
"learning_rate": 4.5e-06,
|
||||||
|
"num_tokens": 277377.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7337374687194824,
|
||||||
|
"rewards/reward_total/std": 0.15055809915065765,
|
||||||
|
"rewards/reward_market/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_market/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10873749852180481,
|
||||||
|
"rewards/reward_showroom/std": 0.06778524816036224,
|
||||||
|
"reward": 0.7337374687194824,
|
||||||
|
"reward_std": 0.15055811405181885,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.719489771152439e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 1.9073031580774114e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999985694885254,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999998807907104,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000019073486328,
|
||||||
|
"entropy": 4.224909940830912e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.26371632888913,
|
||||||
|
"epoch": 0.5555555555555556
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 11,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.00015879125567153096,
|
||||||
|
"learning_rate": 5e-06,
|
||||||
|
"num_tokens": 305332.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7567968368530273,
|
||||||
|
"rewards/reward_total/std": 0.13728150725364685,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_warehouse/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_showroom/mean": 0.10679687559604645,
|
||||||
|
"rewards/reward_showroom/std": 0.07404065877199173,
|
||||||
|
"reward": 0.7567968368530273,
|
||||||
|
"reward_std": 0.13728150725364685,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 3.067227396513772e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.6226434783893637e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999973773956299,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999994039535522,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000019073486328,
|
||||||
|
"entropy": 4.7876037001515215e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.4472255371511,
|
||||||
|
"epoch": 0.6111111111111112
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 12,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.00039661259506829083,
|
||||||
|
"learning_rate": 4.3750000000000005e-06,
|
||||||
|
"num_tokens": 333165.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7081500291824341,
|
||||||
|
"rewards/reward_total/std": 0.1421954482793808,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_warehouse/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_showroom/mean": 0.13315001130104065,
|
||||||
|
"rewards/reward_showroom/std": 0.07370516657829285,
|
||||||
|
"reward": 0.7081500291824341,
|
||||||
|
"reward_std": 0.142195463180542,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.768499479723687e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 5.602954843197949e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999943971633911,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999988675117493,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000016689300537,
|
||||||
|
"entropy": 5.9777358274004655e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.45015063509345,
|
||||||
|
"epoch": 0.6666666666666666
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 13,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.0005282312049530447,
|
||||||
|
"learning_rate": 3.7500000000000005e-06,
|
||||||
|
"num_tokens": 361006.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7762781381607056,
|
||||||
|
"rewards/reward_total/std": 0.13823458552360535,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10127812623977661,
|
||||||
|
"rewards/reward_showroom/std": 0.06158862262964249,
|
||||||
|
"reward": 0.7762781381607056,
|
||||||
|
"reward_std": 0.13823460042476654,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 6.830008487668238e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 5.60290391149465e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999943971633911,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999983310699463,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000022649765015,
|
||||||
|
"entropy": 7.182803437899565e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.955969959497452,
|
||||||
|
"epoch": 0.7222222222222222
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 14,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.000535853614564985,
|
||||||
|
"learning_rate": 3.125e-06,
|
||||||
|
"num_tokens": 388862.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7628874778747559,
|
||||||
|
"rewards/reward_total/std": 0.1295449286699295,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3499999940395355,
|
||||||
|
"rewards/reward_warehouse/std": 0.19674775004386902,
|
||||||
|
"rewards/reward_showroom/mean": 0.11288750171661377,
|
||||||
|
"rewards/reward_showroom/std": 0.073255755007267,
|
||||||
|
"reward": 0.7628874778747559,
|
||||||
|
"reward_std": 0.1295449435710907,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 1.1113726259281975e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.0979605324100703e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999922513961792,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0000004768371582,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000211000442505,
|
||||||
|
"entropy": 9.972968496185786e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.99697282537818,
|
||||||
|
"epoch": 0.7777777777777778
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 15,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.005312301218509674,
|
||||||
|
"learning_rate": 2.5e-06,
|
||||||
|
"num_tokens": 416636.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7899656295776367,
|
||||||
|
"rewards/reward_total/std": 0.1296130269765854,
|
||||||
|
"rewards/reward_market/mean": 0.3499999940395355,
|
||||||
|
"rewards/reward_market/std": 0.19674775004386902,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.08996562659740448,
|
||||||
|
"rewards/reward_showroom/std": 0.05463240668177605,
|
||||||
|
"reward": 0.7899656295776367,
|
||||||
|
"reward_std": 0.12961304187774658,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.004845322924666e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 4.589592936099507e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999337792396545,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999885559082031,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000029802322388,
|
||||||
|
"entropy": 0.0001807671503684105,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.184648096561432,
|
||||||
|
"epoch": 0.8333333333333334
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 16,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.005995223298668861,
|
||||||
|
"learning_rate": 1.8750000000000003e-06,
|
||||||
|
"num_tokens": 444544.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.789996862411499,
|
||||||
|
"rewards/reward_total/std": 0.12048782408237457,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32039374113082886,
|
||||||
|
"rewards/reward_warehouse/std": 0.18316024541854858,
|
||||||
|
"rewards/reward_showroom/mean": 0.09460312128067017,
|
||||||
|
"rewards/reward_showroom/std": 0.062435995787382126,
|
||||||
|
"reward": 0.789996862411499,
|
||||||
|
"reward_std": 0.12048781663179398,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.866625204158481e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.9087463190080598e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.999959409236908,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999855160713196,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000004768371582,
|
||||||
|
"entropy": 0.00019320984370096994,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.476148523390293,
|
||||||
|
"epoch": 0.8888888888888888
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 17,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.011378168128430843,
|
||||||
|
"learning_rate": 1.25e-06,
|
||||||
|
"num_tokens": 472481.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.8168656826019287,
|
||||||
|
"rewards/reward_total/std": 0.09262391924858093,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3498094081878662,
|
||||||
|
"rewards/reward_warehouse/std": 0.19690066576004028,
|
||||||
|
"rewards/reward_showroom/mean": 0.09205625206232071,
|
||||||
|
"rewards/reward_showroom/std": 0.07046373933553696,
|
||||||
|
"reward": 0.8168656826019287,
|
||||||
|
"reward_std": 0.09262390434741974,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 5.950785180175444e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 4.7328881919384e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999284744262695,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999822974205017,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.000001072883606,
|
||||||
|
"entropy": 0.00021975090658088448,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.344543006271124,
|
||||||
|
"epoch": 0.9444444444444444
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 18,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.018683306872844696,
|
||||||
|
"learning_rate": 6.25e-07,
|
||||||
|
"num_tokens": 500266.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7750625014305115,
|
||||||
|
"rewards/reward_total/std": 0.14084643125534058,
|
||||||
|
"rewards/reward_market/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_market/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32499998807907104,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837164342403412,
|
||||||
|
"rewards/reward_showroom/mean": 0.10006250441074371,
|
||||||
|
"rewards/reward_showroom/std": 0.05640558898448944,
|
||||||
|
"reward": 0.7750625014305115,
|
||||||
|
"reward_std": 0.14084644615650177,
|
||||||
|
"frac_reward_zero_std": 0.0625,
|
||||||
|
"sampling/sampling_logp_difference/mean": 1.1303089195280336e-05,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.00027322862297296524,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.999584436416626,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999662637710571,
|
||||||
|
"sampling/importance_sampling_ratio/max": 0.9999997615814209,
|
||||||
|
"entropy": 0.000320568448614722,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.66909484937787,
|
||||||
|
"epoch": 1.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 18,
|
||||||
|
"train_runtime": 406.352,
|
||||||
|
"train_samples_per_second": 0.738,
|
||||||
|
"train_steps_per_second": 0.044,
|
||||||
|
"total_flos": 0.0,
|
||||||
|
"train_loss": 0.016376476217475202,
|
||||||
|
"epoch": 1.0
|
||||||
|
}
|
||||||
|
]
|
||||||
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:872cf55c95f16433857b30a913ba8e0ef062a2b2e5285a59e8521be460dfd22e
|
||||||
|
size 4969539560
|
||||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:42064022b1a0619e4d67470e94808e963991bcbf30ed05fff2ee5e0e1ce2d8dd
|
||||||
|
size 1912795688
|
||||||
318
model.safetensors.index.json
Normal file
318
model.safetensors.index.json
Normal file
@@ -0,0 +1,318 @@
|
|||||||
|
{
|
||||||
|
"metadata": {
|
||||||
|
"total_parameters": 1720574976,
|
||||||
|
"total_size": 6882299904
|
||||||
|
},
|
||||||
|
"weight_map": {
|
||||||
|
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.18.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_norm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_norm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||||
|
}
|
||||||
|
}
|
||||||
BIN
reward_curve.png
Normal file
BIN
reward_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 55 KiB |
BIN
reward_total_curve.png
Normal file
BIN
reward_total_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 56 KiB |
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
|||||||
|
{
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|im_start|>",
|
||||||
|
"<|im_end|>",
|
||||||
|
"<|object_ref_start|>",
|
||||||
|
"<|object_ref_end|>",
|
||||||
|
"<|box_start|>",
|
||||||
|
"<|box_end|>",
|
||||||
|
"<|quad_start|>",
|
||||||
|
"<|quad_end|>",
|
||||||
|
"<|vision_start|>",
|
||||||
|
"<|vision_end|>",
|
||||||
|
"<|vision_pad|>",
|
||||||
|
"<|image_pad|>",
|
||||||
|
"<|video_pad|>"
|
||||||
|
],
|
||||||
|
"eos_token": {
|
||||||
|
"content": "<|im_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"pad_token": {
|
||||||
|
"content": "<|endoftext|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
}
|
||||||
|
}
|
||||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
|||||||
|
{
|
||||||
|
"add_bos_token": false,
|
||||||
|
"add_prefix_space": false,
|
||||||
|
"added_tokens_decoder": {
|
||||||
|
"151643": {
|
||||||
|
"content": "<|endoftext|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151644": {
|
||||||
|
"content": "<|im_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151645": {
|
||||||
|
"content": "<|im_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151646": {
|
||||||
|
"content": "<|object_ref_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151647": {
|
||||||
|
"content": "<|object_ref_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151648": {
|
||||||
|
"content": "<|box_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151649": {
|
||||||
|
"content": "<|box_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151650": {
|
||||||
|
"content": "<|quad_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151651": {
|
||||||
|
"content": "<|quad_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151652": {
|
||||||
|
"content": "<|vision_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151653": {
|
||||||
|
"content": "<|vision_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151654": {
|
||||||
|
"content": "<|vision_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151655": {
|
||||||
|
"content": "<|image_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151656": {
|
||||||
|
"content": "<|video_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151657": {
|
||||||
|
"content": "<tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151658": {
|
||||||
|
"content": "</tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151659": {
|
||||||
|
"content": "<|fim_prefix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151660": {
|
||||||
|
"content": "<|fim_middle|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151661": {
|
||||||
|
"content": "<|fim_suffix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151662": {
|
||||||
|
"content": "<|fim_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151663": {
|
||||||
|
"content": "<|repo_name|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151664": {
|
||||||
|
"content": "<|file_sep|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151665": {
|
||||||
|
"content": "<tool_response>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151666": {
|
||||||
|
"content": "</tool_response>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151667": {
|
||||||
|
"content": "<think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151668": {
|
||||||
|
"content": "</think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|im_start|>",
|
||||||
|
"<|im_end|>",
|
||||||
|
"<|object_ref_start|>",
|
||||||
|
"<|object_ref_end|>",
|
||||||
|
"<|box_start|>",
|
||||||
|
"<|box_end|>",
|
||||||
|
"<|quad_start|>",
|
||||||
|
"<|quad_end|>",
|
||||||
|
"<|vision_start|>",
|
||||||
|
"<|vision_end|>",
|
||||||
|
"<|vision_pad|>",
|
||||||
|
"<|image_pad|>",
|
||||||
|
"<|video_pad|>"
|
||||||
|
],
|
||||||
|
"bos_token": null,
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"model_max_length": 131072,
|
||||||
|
"pad_token": "<|endoftext|>",
|
||||||
|
"split_special_tokens": false,
|
||||||
|
"tokenizer_class": "Qwen2Tokenizer",
|
||||||
|
"unk_token": null
|
||||||
|
}
|
||||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:cbe511346c8e8eb82c82026e6fd1f3d690b168b42eb535a5255b06536b0a5a08
|
||||||
|
size 7953
|
||||||
BIN
training_artifacts/loss_curve.png
Normal file
BIN
training_artifacts/loss_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 40 KiB |
20
training_artifacts/metrics.csv
Normal file
20
training_artifacts/metrics.csv
Normal file
@@ -0,0 +1,20 @@
|
|||||||
|
step,loss,grad_norm,learning_rate,num_tokens,completions/mean_length,completions/min_length,completions/max_length,completions/clipped_ratio,completions/mean_terminated_length,completions/min_terminated_length,completions/max_terminated_length,rewards/reward_total/mean,rewards/reward_total/std,rewards/reward_market/mean,rewards/reward_market/std,rewards/reward_warehouse/mean,rewards/reward_warehouse/std,rewards/reward_showroom/mean,rewards/reward_showroom/std,reward,reward_std,frac_reward_zero_std,sampling/sampling_logp_difference/mean,sampling/sampling_logp_difference/max,sampling/importance_sampling_ratio/min,sampling/importance_sampling_ratio/mean,sampling/importance_sampling_ratio/max,entropy,clip_ratio/low_mean,clip_ratio/low_min,clip_ratio/high_mean,clip_ratio/high_max,clip_ratio/region_mean,step_time,epoch,train_runtime,train_samples_per_second,train_steps_per_second,total_flos,train_loss
|
||||||
|
1,-0.009,12.235088348388672,0.0,27758.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7793656587600708,0.12745577096939087,0.25,0.13440430164337158,0.42500001192092896,0.20160645246505737,0.10436563193798065,0.069697305560112,0.7793656587600708,0.12745577096939087,0.0,0.005470390431582928,0.22214925289154053,0.8007970452308655,0.9949374794960022,1.076386570930481,0.028439456821217846,0.0,0.0,0.0,0.0,0.0,19.228480510413647,0.05555555555555555,,,,,
|
||||||
|
2,0.0723,60.551937103271484,5.000000000000001e-07,55324.0,3.25,3.0,7.0,0.0,3.25,3.0,7.0,0.719434380531311,0.1505809724330902,0.30000001192092896,0.17597654461860657,0.30000001192092896,0.17597654461860657,0.11943437159061432,0.07055392116308212,0.719434380531311,0.1505809724330902,0.0,0.01085888221859932,0.28092825412750244,0.8382877111434937,1.0260276794433594,1.324359655380249,0.036137547835437545,0.0,0.0,0.0,0.0,0.0,17.92062332853675,0.1111111111111111,,,,,
|
||||||
|
3,0.1153,232.934814453125,1.0000000000000002e-06,83000.0,3.5,3.0,7.0,0.0,3.5,3.0,7.0,0.7885687351226807,0.1279384195804596,0.32500001788139343,0.18837162852287292,0.375,0.20160646736621857,0.08856874704360962,0.07010025531053543,0.7885687351226807,0.1279384344816208,0.0,0.0251829382032156,0.6850378513336182,0.5226751565933228,1.0358223915100098,1.9838452339172363,0.03248842835137111,0.0,0.0,0.0,0.0,0.0,17.184778176248074,0.16666666666666666,,,,,
|
||||||
|
4,0.0243,13.620709419250488,1.5e-06,110708.0,3.125,3.0,7.0,0.0,3.125,3.0,7.0,0.7762374877929688,0.13016164302825928,0.32499998807907104,0.18837164342403412,0.3500000238418579,0.1967477649450302,0.10123749077320099,0.06825561076402664,0.7762374877929688,0.13016162812709808,0.0,0.007013080175966024,0.2646750509738922,0.7674550414085388,0.9837819337844849,1.0260045528411865,0.03743034108288157,0.0,0.0,0.0,0.0,0.0,17.90316915512085,0.2222222222222222,,,,,
|
||||||
|
5,0.0004,2.0591225624084473,2.0000000000000003e-06,138452.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7784374952316284,0.12858590483665466,0.30000001192092896,0.17597654461860657,0.375,0.20160646736621857,0.10343749821186066,0.06380020827054977,0.7784374952316284,0.12858593463897705,0.0,0.001465568202547729,0.05673474818468094,0.9749767780303955,1.0017430782318115,1.058376669883728,0.008188390799773515,0.0,0.0,0.0,0.0,0.0,17.8210555203259,0.2777777777777778,,,,,
|
||||||
|
6,0.0915,31.611696243286133,2.5e-06,166252.0,3.125,3.0,7.0,0.0,3.125,3.0,7.0,0.7915937900543213,0.12960509955883026,0.375,0.20160646736621857,0.32500001788139343,0.18837162852287292,0.09159374982118607,0.0639258474111557,0.7915937900543213,0.12960509955883026,0.0,0.008641102351248264,0.8236088752746582,0.9935171008110046,1.0399717092514038,2.278707504272461,0.007084679029730978,0.0,0.0,0.0,0.0,0.0,18.056264080107212,0.3333333333333333,,,,,
|
||||||
|
7,-0.0,0.281630277633667,3e-06,193950.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7600874900817871,0.13816162943840027,0.32500001788139343,0.18837162852287292,0.32500001788139343,0.18837162852287292,0.11008749902248383,0.07028691470623016,0.7600874900817871,0.13816164433956146,0.0,3.554227441782132e-05,0.0027569520752876997,0.997247576713562,0.9999052286148071,1.0000724792480469,0.0005298306713825696,0.0,0.0,0.0,0.0,0.0,17.43799263238907,0.3888888888888889,,,,,
|
||||||
|
8,0.0,0.00018881642608903348,3.5e-06,221677.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7622687816619873,0.1372590959072113,0.4000000059604645,0.20320022106170654,0.25,0.13440430164337158,0.11226874589920044,0.07360353320837021,0.7622687816619873,0.1372590959072113,0.0,2.545601773817907e-07,1.5496943888138048e-06,0.9999986886978149,1.000000238418579,1.0000016689300537,4.1391018498870835e-05,0.0,0.0,0.0,0.0,0.0,17.406394600868225,0.4444444444444444,,,,,
|
||||||
|
9,0.0,0.00015632262511644512,4.000000000000001e-06,249549.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.775946855545044,0.137176051735878,0.375,0.20160646736621857,0.30000001192092896,0.17597654461860657,0.10094687342643738,0.058497413992881775,0.775946855545044,0.1371760368347168,0.0,2.918131087881193e-07,3.099441755693988e-06,0.9999978542327881,1.0,1.000001311302185,4.173239403826301e-05,0.0,0.0,0.0,0.0,0.0,18.514019537717104,0.5,,,,,
|
||||||
|
10,0.0,9.833038348006085e-05,4.5e-06,277377.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7337374687194824,0.15055809915065765,0.2750000059604645,0.1586231142282486,0.3500000238418579,0.1967477649450302,0.10873749852180481,0.06778524816036224,0.7337374687194824,0.15055811405181885,0.0,2.719489771152439e-07,1.9073031580774114e-06,0.9999985694885254,0.9999998807907104,1.0000019073486328,4.224909940830912e-05,0.0,0.0,0.0,0.0,0.0,18.26371632888913,0.5555555555555556,,,,,
|
||||||
|
11,-0.0,0.00015879125567153096,5e-06,305332.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7567968368530273,0.13728150725364685,0.375,0.20160646736621857,0.2750000059604645,0.1586231142282486,0.10679687559604645,0.07404065877199173,0.7567968368530273,0.13728150725364685,0.0,3.067227396513772e-07,2.6226434783893637e-06,0.9999973773956299,0.9999994039535522,1.0000019073486328,4.7876037001515215e-05,0.0,0.0,0.0,0.0,0.0,19.4472255371511,0.6111111111111112,,,,,
|
||||||
|
12,-0.0,0.00039661259506829083,4.3750000000000005e-06,333165.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7081500291824341,0.1421954482793808,0.30000001192092896,0.17597654461860657,0.2750000059604645,0.1586231142282486,0.13315001130104065,0.07370516657829285,0.7081500291824341,0.142195463180542,0.0,4.768499479723687e-07,5.602954843197949e-06,0.9999943971633911,0.9999988675117493,1.0000016689300537,5.9777358274004655e-05,0.0,0.0,0.0,0.0,0.0,18.45015063509345,0.6666666666666666,,,,,
|
||||||
|
13,0.0,0.0005282312049530447,3.7500000000000005e-06,361006.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7762781381607056,0.13823458552360535,0.32500001788139343,0.18837162852287292,0.3500000238418579,0.1967477649450302,0.10127812623977661,0.06158862262964249,0.7762781381607056,0.13823460042476654,0.0,6.830008487668238e-07,5.60290391149465e-06,0.9999943971633911,0.9999983310699463,1.0000022649765015,7.182803437899565e-05,0.0,0.0,0.0,0.0,0.0,17.955969959497452,0.7222222222222222,,,,,
|
||||||
|
14,-0.0,0.000535853614564985,3.125e-06,388862.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7628874778747559,0.1295449286699295,0.30000001192092896,0.17597654461860657,0.3499999940395355,0.19674775004386902,0.11288750171661377,0.073255755007267,0.7628874778747559,0.1295449435710907,0.0,1.1113726259281975e-06,2.0979605324100703e-05,0.9999922513961792,1.0000004768371582,1.0000211000442505,9.972968496185786e-05,0.0,0.0,0.0,0.0,0.0,18.99697282537818,0.7777777777777778,,,,,
|
||||||
|
15,0.0,0.005312301218509674,2.5e-06,416636.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7899656295776367,0.1296130269765854,0.3499999940395355,0.19674775004386902,0.3500000238418579,0.1967477649450302,0.08996562659740448,0.05463240668177605,0.7899656295776367,0.12961304187774658,0.0,4.004845322924666e-06,4.589592936099507e-05,0.9999337792396545,0.9999885559082031,1.0000029802322388,0.0001807671503684105,0.0,0.0,0.0,0.0,0.0,19.184648096561432,0.8333333333333334,,,,,
|
||||||
|
16,-0.0,0.005995223298668861,1.8750000000000003e-06,444544.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.789996862411499,0.12048782408237457,0.375,0.20160646736621857,0.32039374113082886,0.18316024541854858,0.09460312128067017,0.062435995787382126,0.789996862411499,0.12048781663179398,0.0,4.866625204158481e-06,2.9087463190080598e-05,0.999959409236908,0.9999855160713196,1.0000004768371582,0.00019320984370096994,0.0,0.0,0.0,0.0,0.0,19.476148523390293,0.8888888888888888,,,,,
|
||||||
|
17,0.0,0.011378168128430843,1.25e-06,472481.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.8168656826019287,0.09262391924858093,0.375,0.20160646736621857,0.3498094081878662,0.19690066576004028,0.09205625206232071,0.07046373933553696,0.8168656826019287,0.09262390434741974,0.0,5.950785180175444e-06,4.7328881919384e-05,0.9999284744262695,0.9999822974205017,1.000001072883606,0.00021975090658088448,0.0,0.0,0.0,0.0,0.0,19.344543006271124,0.9444444444444444,,,,,
|
||||||
|
18,0.0,0.018683306872844696,6.25e-07,500266.0,3.0,3.0,3.0,0.0,3.0,3.0,3.0,0.7750625014305115,0.14084643125534058,0.3500000238418579,0.1967477649450302,0.32499998807907104,0.18837164342403412,0.10006250441074371,0.05640558898448944,0.7750625014305115,0.14084644615650177,0.0625,1.1303089195280336e-05,0.00027322862297296524,0.999584436416626,0.9999662637710571,0.9999997615814209,0.000320568448614722,0.0,0.0,0.0,0.0,0.0,17.66909484937787,1.0,,,,,
|
||||||
|
18,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1.0,406.352,0.738,0.044,0.0,0.016376476217475202
|
||||||
|
695
training_artifacts/metrics.json
Normal file
695
training_artifacts/metrics.json
Normal file
@@ -0,0 +1,695 @@
|
|||||||
|
[
|
||||||
|
{
|
||||||
|
"step": 1,
|
||||||
|
"loss": -0.009,
|
||||||
|
"grad_norm": 12.235088348388672,
|
||||||
|
"learning_rate": 0.0,
|
||||||
|
"num_tokens": 27758.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7793656587600708,
|
||||||
|
"rewards/reward_total/std": 0.12745577096939087,
|
||||||
|
"rewards/reward_market/mean": 0.25,
|
||||||
|
"rewards/reward_market/std": 0.13440430164337158,
|
||||||
|
"rewards/reward_warehouse/mean": 0.42500001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160645246505737,
|
||||||
|
"rewards/reward_showroom/mean": 0.10436563193798065,
|
||||||
|
"rewards/reward_showroom/std": 0.069697305560112,
|
||||||
|
"reward": 0.7793656587600708,
|
||||||
|
"reward_std": 0.12745577096939087,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.005470390431582928,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.22214925289154053,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.8007970452308655,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9949374794960022,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.076386570930481,
|
||||||
|
"entropy": 0.028439456821217846,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.228480510413647,
|
||||||
|
"epoch": 0.05555555555555555
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 2,
|
||||||
|
"loss": 0.0723,
|
||||||
|
"grad_norm": 60.551937103271484,
|
||||||
|
"learning_rate": 5.000000000000001e-07,
|
||||||
|
"num_tokens": 55324.0,
|
||||||
|
"completions/mean_length": 3.25,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.25,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.719434380531311,
|
||||||
|
"rewards/reward_total/std": 0.1505809724330902,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_showroom/mean": 0.11943437159061432,
|
||||||
|
"rewards/reward_showroom/std": 0.07055392116308212,
|
||||||
|
"reward": 0.719434380531311,
|
||||||
|
"reward_std": 0.1505809724330902,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.01085888221859932,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.28092825412750244,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.8382877111434937,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0260276794433594,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.324359655380249,
|
||||||
|
"entropy": 0.036137547835437545,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.92062332853675,
|
||||||
|
"epoch": 0.1111111111111111
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 3,
|
||||||
|
"loss": 0.1153,
|
||||||
|
"grad_norm": 232.934814453125,
|
||||||
|
"learning_rate": 1.0000000000000002e-06,
|
||||||
|
"num_tokens": 83000.0,
|
||||||
|
"completions/mean_length": 3.5,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.5,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7885687351226807,
|
||||||
|
"rewards/reward_total/std": 0.1279384195804596,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.375,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_showroom/mean": 0.08856874704360962,
|
||||||
|
"rewards/reward_showroom/std": 0.07010025531053543,
|
||||||
|
"reward": 0.7885687351226807,
|
||||||
|
"reward_std": 0.1279384344816208,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.0251829382032156,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.6850378513336182,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.5226751565933228,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0358223915100098,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.9838452339172363,
|
||||||
|
"entropy": 0.03248842835137111,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.184778176248074,
|
||||||
|
"epoch": 0.16666666666666666
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 4,
|
||||||
|
"loss": 0.0243,
|
||||||
|
"grad_norm": 13.620709419250488,
|
||||||
|
"learning_rate": 1.5e-06,
|
||||||
|
"num_tokens": 110708.0,
|
||||||
|
"completions/mean_length": 3.125,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.125,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7762374877929688,
|
||||||
|
"rewards/reward_total/std": 0.13016164302825928,
|
||||||
|
"rewards/reward_market/mean": 0.32499998807907104,
|
||||||
|
"rewards/reward_market/std": 0.18837164342403412,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10123749077320099,
|
||||||
|
"rewards/reward_showroom/std": 0.06825561076402664,
|
||||||
|
"reward": 0.7762374877929688,
|
||||||
|
"reward_std": 0.13016162812709808,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.007013080175966024,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.2646750509738922,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.7674550414085388,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9837819337844849,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0260045528411865,
|
||||||
|
"entropy": 0.03743034108288157,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.90316915512085,
|
||||||
|
"epoch": 0.2222222222222222
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 5,
|
||||||
|
"loss": 0.0004,
|
||||||
|
"grad_norm": 2.0591225624084473,
|
||||||
|
"learning_rate": 2.0000000000000003e-06,
|
||||||
|
"num_tokens": 138452.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7784374952316284,
|
||||||
|
"rewards/reward_total/std": 0.12858590483665466,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.375,
|
||||||
|
"rewards/reward_warehouse/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_showroom/mean": 0.10343749821186066,
|
||||||
|
"rewards/reward_showroom/std": 0.06380020827054977,
|
||||||
|
"reward": 0.7784374952316284,
|
||||||
|
"reward_std": 0.12858593463897705,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.001465568202547729,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.05673474818468094,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9749767780303955,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0017430782318115,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.058376669883728,
|
||||||
|
"entropy": 0.008188390799773515,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.8210555203259,
|
||||||
|
"epoch": 0.2777777777777778
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 6,
|
||||||
|
"loss": 0.0915,
|
||||||
|
"grad_norm": 31.611696243286133,
|
||||||
|
"learning_rate": 2.5e-06,
|
||||||
|
"num_tokens": 166252.0,
|
||||||
|
"completions/mean_length": 3.125,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 7.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.125,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 7.0,
|
||||||
|
"rewards/reward_total/mean": 0.7915937900543213,
|
||||||
|
"rewards/reward_total/std": 0.12960509955883026,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_showroom/mean": 0.09159374982118607,
|
||||||
|
"rewards/reward_showroom/std": 0.0639258474111557,
|
||||||
|
"reward": 0.7915937900543213,
|
||||||
|
"reward_std": 0.12960509955883026,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 0.008641102351248264,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.8236088752746582,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9935171008110046,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0399717092514038,
|
||||||
|
"sampling/importance_sampling_ratio/max": 2.278707504272461,
|
||||||
|
"entropy": 0.007084679029730978,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.056264080107212,
|
||||||
|
"epoch": 0.3333333333333333
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 7,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.281630277633667,
|
||||||
|
"learning_rate": 3e-06,
|
||||||
|
"num_tokens": 193950.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7600874900817871,
|
||||||
|
"rewards/reward_total/std": 0.13816162943840027,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_showroom/mean": 0.11008749902248383,
|
||||||
|
"rewards/reward_showroom/std": 0.07028691470623016,
|
||||||
|
"reward": 0.7600874900817871,
|
||||||
|
"reward_std": 0.13816164433956146,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 3.554227441782132e-05,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.0027569520752876997,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.997247576713562,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999052286148071,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000724792480469,
|
||||||
|
"entropy": 0.0005298306713825696,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.43799263238907,
|
||||||
|
"epoch": 0.3888888888888889
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 8,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.00018881642608903348,
|
||||||
|
"learning_rate": 3.5e-06,
|
||||||
|
"num_tokens": 221677.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7622687816619873,
|
||||||
|
"rewards/reward_total/std": 0.1372590959072113,
|
||||||
|
"rewards/reward_market/mean": 0.4000000059604645,
|
||||||
|
"rewards/reward_market/std": 0.20320022106170654,
|
||||||
|
"rewards/reward_warehouse/mean": 0.25,
|
||||||
|
"rewards/reward_warehouse/std": 0.13440430164337158,
|
||||||
|
"rewards/reward_showroom/mean": 0.11226874589920044,
|
||||||
|
"rewards/reward_showroom/std": 0.07360353320837021,
|
||||||
|
"reward": 0.7622687816619873,
|
||||||
|
"reward_std": 0.1372590959072113,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.545601773817907e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 1.5496943888138048e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999986886978149,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.000000238418579,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000016689300537,
|
||||||
|
"entropy": 4.1391018498870835e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.406394600868225,
|
||||||
|
"epoch": 0.4444444444444444
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 9,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.00015632262511644512,
|
||||||
|
"learning_rate": 4.000000000000001e-06,
|
||||||
|
"num_tokens": 249549.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.775946855545044,
|
||||||
|
"rewards/reward_total/std": 0.137176051735878,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_warehouse/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_showroom/mean": 0.10094687342643738,
|
||||||
|
"rewards/reward_showroom/std": 0.058497413992881775,
|
||||||
|
"reward": 0.775946855545044,
|
||||||
|
"reward_std": 0.1371760368347168,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.918131087881193e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 3.099441755693988e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999978542327881,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.000001311302185,
|
||||||
|
"entropy": 4.173239403826301e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.514019537717104,
|
||||||
|
"epoch": 0.5
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 10,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 9.833038348006085e-05,
|
||||||
|
"learning_rate": 4.5e-06,
|
||||||
|
"num_tokens": 277377.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7337374687194824,
|
||||||
|
"rewards/reward_total/std": 0.15055809915065765,
|
||||||
|
"rewards/reward_market/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_market/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10873749852180481,
|
||||||
|
"rewards/reward_showroom/std": 0.06778524816036224,
|
||||||
|
"reward": 0.7337374687194824,
|
||||||
|
"reward_std": 0.15055811405181885,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 2.719489771152439e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 1.9073031580774114e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999985694885254,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999998807907104,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000019073486328,
|
||||||
|
"entropy": 4.224909940830912e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.26371632888913,
|
||||||
|
"epoch": 0.5555555555555556
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 11,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.00015879125567153096,
|
||||||
|
"learning_rate": 5e-06,
|
||||||
|
"num_tokens": 305332.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7567968368530273,
|
||||||
|
"rewards/reward_total/std": 0.13728150725364685,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_warehouse/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_showroom/mean": 0.10679687559604645,
|
||||||
|
"rewards/reward_showroom/std": 0.07404065877199173,
|
||||||
|
"reward": 0.7567968368530273,
|
||||||
|
"reward_std": 0.13728150725364685,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 3.067227396513772e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.6226434783893637e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999973773956299,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999994039535522,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000019073486328,
|
||||||
|
"entropy": 4.7876037001515215e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.4472255371511,
|
||||||
|
"epoch": 0.6111111111111112
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 12,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.00039661259506829083,
|
||||||
|
"learning_rate": 4.3750000000000005e-06,
|
||||||
|
"num_tokens": 333165.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7081500291824341,
|
||||||
|
"rewards/reward_total/std": 0.1421954482793808,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.2750000059604645,
|
||||||
|
"rewards/reward_warehouse/std": 0.1586231142282486,
|
||||||
|
"rewards/reward_showroom/mean": 0.13315001130104065,
|
||||||
|
"rewards/reward_showroom/std": 0.07370516657829285,
|
||||||
|
"reward": 0.7081500291824341,
|
||||||
|
"reward_std": 0.142195463180542,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.768499479723687e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 5.602954843197949e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999943971633911,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999988675117493,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000016689300537,
|
||||||
|
"entropy": 5.9777358274004655e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.45015063509345,
|
||||||
|
"epoch": 0.6666666666666666
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 13,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.0005282312049530447,
|
||||||
|
"learning_rate": 3.7500000000000005e-06,
|
||||||
|
"num_tokens": 361006.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7762781381607056,
|
||||||
|
"rewards/reward_total/std": 0.13823458552360535,
|
||||||
|
"rewards/reward_market/mean": 0.32500001788139343,
|
||||||
|
"rewards/reward_market/std": 0.18837162852287292,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.10127812623977661,
|
||||||
|
"rewards/reward_showroom/std": 0.06158862262964249,
|
||||||
|
"reward": 0.7762781381607056,
|
||||||
|
"reward_std": 0.13823460042476654,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 6.830008487668238e-07,
|
||||||
|
"sampling/sampling_logp_difference/max": 5.60290391149465e-06,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999943971633911,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999983310699463,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000022649765015,
|
||||||
|
"entropy": 7.182803437899565e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.955969959497452,
|
||||||
|
"epoch": 0.7222222222222222
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 14,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.000535853614564985,
|
||||||
|
"learning_rate": 3.125e-06,
|
||||||
|
"num_tokens": 388862.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7628874778747559,
|
||||||
|
"rewards/reward_total/std": 0.1295449286699295,
|
||||||
|
"rewards/reward_market/mean": 0.30000001192092896,
|
||||||
|
"rewards/reward_market/std": 0.17597654461860657,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3499999940395355,
|
||||||
|
"rewards/reward_warehouse/std": 0.19674775004386902,
|
||||||
|
"rewards/reward_showroom/mean": 0.11288750171661377,
|
||||||
|
"rewards/reward_showroom/std": 0.073255755007267,
|
||||||
|
"reward": 0.7628874778747559,
|
||||||
|
"reward_std": 0.1295449435710907,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 1.1113726259281975e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.0979605324100703e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999922513961792,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 1.0000004768371582,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000211000442505,
|
||||||
|
"entropy": 9.972968496185786e-05,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 18.99697282537818,
|
||||||
|
"epoch": 0.7777777777777778
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 15,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.005312301218509674,
|
||||||
|
"learning_rate": 2.5e-06,
|
||||||
|
"num_tokens": 416636.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7899656295776367,
|
||||||
|
"rewards/reward_total/std": 0.1296130269765854,
|
||||||
|
"rewards/reward_market/mean": 0.3499999940395355,
|
||||||
|
"rewards/reward_market/std": 0.19674775004386902,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_warehouse/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_showroom/mean": 0.08996562659740448,
|
||||||
|
"rewards/reward_showroom/std": 0.05463240668177605,
|
||||||
|
"reward": 0.7899656295776367,
|
||||||
|
"reward_std": 0.12961304187774658,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.004845322924666e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 4.589592936099507e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999337792396545,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999885559082031,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000029802322388,
|
||||||
|
"entropy": 0.0001807671503684105,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.184648096561432,
|
||||||
|
"epoch": 0.8333333333333334
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 16,
|
||||||
|
"loss": -0.0,
|
||||||
|
"grad_norm": 0.005995223298668861,
|
||||||
|
"learning_rate": 1.8750000000000003e-06,
|
||||||
|
"num_tokens": 444544.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.789996862411499,
|
||||||
|
"rewards/reward_total/std": 0.12048782408237457,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32039374113082886,
|
||||||
|
"rewards/reward_warehouse/std": 0.18316024541854858,
|
||||||
|
"rewards/reward_showroom/mean": 0.09460312128067017,
|
||||||
|
"rewards/reward_showroom/std": 0.062435995787382126,
|
||||||
|
"reward": 0.789996862411499,
|
||||||
|
"reward_std": 0.12048781663179398,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 4.866625204158481e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 2.9087463190080598e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.999959409236908,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999855160713196,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.0000004768371582,
|
||||||
|
"entropy": 0.00019320984370096994,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.476148523390293,
|
||||||
|
"epoch": 0.8888888888888888
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 17,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.011378168128430843,
|
||||||
|
"learning_rate": 1.25e-06,
|
||||||
|
"num_tokens": 472481.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.8168656826019287,
|
||||||
|
"rewards/reward_total/std": 0.09262391924858093,
|
||||||
|
"rewards/reward_market/mean": 0.375,
|
||||||
|
"rewards/reward_market/std": 0.20160646736621857,
|
||||||
|
"rewards/reward_warehouse/mean": 0.3498094081878662,
|
||||||
|
"rewards/reward_warehouse/std": 0.19690066576004028,
|
||||||
|
"rewards/reward_showroom/mean": 0.09205625206232071,
|
||||||
|
"rewards/reward_showroom/std": 0.07046373933553696,
|
||||||
|
"reward": 0.8168656826019287,
|
||||||
|
"reward_std": 0.09262390434741974,
|
||||||
|
"frac_reward_zero_std": 0.0,
|
||||||
|
"sampling/sampling_logp_difference/mean": 5.950785180175444e-06,
|
||||||
|
"sampling/sampling_logp_difference/max": 4.7328881919384e-05,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.9999284744262695,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999822974205017,
|
||||||
|
"sampling/importance_sampling_ratio/max": 1.000001072883606,
|
||||||
|
"entropy": 0.00021975090658088448,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 19.344543006271124,
|
||||||
|
"epoch": 0.9444444444444444
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 18,
|
||||||
|
"loss": 0.0,
|
||||||
|
"grad_norm": 0.018683306872844696,
|
||||||
|
"learning_rate": 6.25e-07,
|
||||||
|
"num_tokens": 500266.0,
|
||||||
|
"completions/mean_length": 3.0,
|
||||||
|
"completions/min_length": 3.0,
|
||||||
|
"completions/max_length": 3.0,
|
||||||
|
"completions/clipped_ratio": 0.0,
|
||||||
|
"completions/mean_terminated_length": 3.0,
|
||||||
|
"completions/min_terminated_length": 3.0,
|
||||||
|
"completions/max_terminated_length": 3.0,
|
||||||
|
"rewards/reward_total/mean": 0.7750625014305115,
|
||||||
|
"rewards/reward_total/std": 0.14084643125534058,
|
||||||
|
"rewards/reward_market/mean": 0.3500000238418579,
|
||||||
|
"rewards/reward_market/std": 0.1967477649450302,
|
||||||
|
"rewards/reward_warehouse/mean": 0.32499998807907104,
|
||||||
|
"rewards/reward_warehouse/std": 0.18837164342403412,
|
||||||
|
"rewards/reward_showroom/mean": 0.10006250441074371,
|
||||||
|
"rewards/reward_showroom/std": 0.05640558898448944,
|
||||||
|
"reward": 0.7750625014305115,
|
||||||
|
"reward_std": 0.14084644615650177,
|
||||||
|
"frac_reward_zero_std": 0.0625,
|
||||||
|
"sampling/sampling_logp_difference/mean": 1.1303089195280336e-05,
|
||||||
|
"sampling/sampling_logp_difference/max": 0.00027322862297296524,
|
||||||
|
"sampling/importance_sampling_ratio/min": 0.999584436416626,
|
||||||
|
"sampling/importance_sampling_ratio/mean": 0.9999662637710571,
|
||||||
|
"sampling/importance_sampling_ratio/max": 0.9999997615814209,
|
||||||
|
"entropy": 0.000320568448614722,
|
||||||
|
"clip_ratio/low_mean": 0.0,
|
||||||
|
"clip_ratio/low_min": 0.0,
|
||||||
|
"clip_ratio/high_mean": 0.0,
|
||||||
|
"clip_ratio/high_max": 0.0,
|
||||||
|
"clip_ratio/region_mean": 0.0,
|
||||||
|
"step_time": 17.66909484937787,
|
||||||
|
"epoch": 1.0
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"step": 18,
|
||||||
|
"train_runtime": 406.352,
|
||||||
|
"train_samples_per_second": 0.738,
|
||||||
|
"train_steps_per_second": 0.044,
|
||||||
|
"total_flos": 0.0,
|
||||||
|
"train_loss": 0.016376476217475202,
|
||||||
|
"epoch": 1.0
|
||||||
|
}
|
||||||
|
]
|
||||||
BIN
training_artifacts/reward_curve.png
Normal file
BIN
training_artifacts/reward_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 55 KiB |
BIN
training_artifacts/reward_total_curve.png
Normal file
BIN
training_artifacts/reward_total_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 56 KiB |
63
training_artifacts/training_summary.json
Normal file
63
training_artifacts/training_summary.json
Normal file
@@ -0,0 +1,63 @@
|
|||||||
|
{
|
||||||
|
"loss": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.1153,
|
||||||
|
"min": -0.009,
|
||||||
|
"mean": 0.01637777777777778,
|
||||||
|
"n": 18
|
||||||
|
},
|
||||||
|
"reward_total": {
|
||||||
|
"final": 0.7750625014305115,
|
||||||
|
"max": 0.8168656826019287,
|
||||||
|
"min": 0.7081500291824341,
|
||||||
|
"mean": 0.7689822945329878,
|
||||||
|
"n": 18
|
||||||
|
},
|
||||||
|
"reward_market": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"reward_warehouse": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"reward_showroom": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"n_log_rows": 19,
|
||||||
|
"output_dir": "/workspace/shopmanager-grpo-qwen3",
|
||||||
|
"run_config": {
|
||||||
|
"model": "Qwen/Qwen3-1.7B",
|
||||||
|
"env_url": "https://hard007ik-shopmanagereng.hf.space",
|
||||||
|
"dataset_size": 300,
|
||||||
|
"num_generations": 2,
|
||||||
|
"per_device_batch": 1,
|
||||||
|
"grad_accum": 32,
|
||||||
|
"max_completion_length": 64,
|
||||||
|
"max_turns": 15,
|
||||||
|
"lr": 5e-06,
|
||||||
|
"warmup_steps": 10,
|
||||||
|
"max_steps": -1,
|
||||||
|
"epochs": 1,
|
||||||
|
"vllm_gpu_mem": 0.3,
|
||||||
|
"reward_weights": [
|
||||||
|
1.0,
|
||||||
|
0.0,
|
||||||
|
0.0,
|
||||||
|
0.0
|
||||||
|
],
|
||||||
|
"precision": {
|
||||||
|
"bf16": true
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
63
training_summary.json
Normal file
63
training_summary.json
Normal file
@@ -0,0 +1,63 @@
|
|||||||
|
{
|
||||||
|
"loss": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.1153,
|
||||||
|
"min": -0.009,
|
||||||
|
"mean": 0.01637777777777778,
|
||||||
|
"n": 18
|
||||||
|
},
|
||||||
|
"reward_total": {
|
||||||
|
"final": 0.7750625014305115,
|
||||||
|
"max": 0.8168656826019287,
|
||||||
|
"min": 0.7081500291824341,
|
||||||
|
"mean": 0.7689822945329878,
|
||||||
|
"n": 18
|
||||||
|
},
|
||||||
|
"reward_market": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"reward_warehouse": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"reward_showroom": {
|
||||||
|
"final": 0.0,
|
||||||
|
"max": 0.0,
|
||||||
|
"min": 0.0,
|
||||||
|
"mean": 0.0,
|
||||||
|
"n": 0
|
||||||
|
},
|
||||||
|
"n_log_rows": 19,
|
||||||
|
"output_dir": "/workspace/shopmanager-grpo-qwen3",
|
||||||
|
"run_config": {
|
||||||
|
"model": "Qwen/Qwen3-1.7B",
|
||||||
|
"env_url": "https://hard007ik-shopmanagereng.hf.space",
|
||||||
|
"dataset_size": 300,
|
||||||
|
"num_generations": 2,
|
||||||
|
"per_device_batch": 1,
|
||||||
|
"grad_accum": 32,
|
||||||
|
"max_completion_length": 64,
|
||||||
|
"max_turns": 15,
|
||||||
|
"lr": 5e-06,
|
||||||
|
"warmup_steps": 10,
|
||||||
|
"max_steps": -1,
|
||||||
|
"epochs": 1,
|
||||||
|
"vllm_gpu_mem": 0.3,
|
||||||
|
"reward_weights": [
|
||||||
|
1.0,
|
||||||
|
0.0,
|
||||||
|
0.0,
|
||||||
|
0.0
|
||||||
|
],
|
||||||
|
"precision": {
|
||||||
|
"bf16": true
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user