初始化项目,由ModelHub XC社区提供模型
Model: karthik-2905/AL1-model-B Source: Original Platform
This commit is contained in:
209
adapters/sft-lora/checkpoint-90/README.md
Normal file
209
adapters/sft-lora/checkpoint-90/README.md
Normal file
@@ -0,0 +1,209 @@
|
||||
---
|
||||
base_model: Qwen/Qwen3-0.6B
|
||||
library_name: peft
|
||||
pipeline_tag: text-generation
|
||||
tags:
|
||||
- base_model:adapter:Qwen/Qwen3-0.6B
|
||||
- lora
|
||||
- sft
|
||||
- transformers
|
||||
- trl
|
||||
---
|
||||
|
||||
# Model Card for Model ID
|
||||
|
||||
<!-- Provide a quick summary of what the model is/does. -->
|
||||
|
||||
|
||||
|
||||
## Model Details
|
||||
|
||||
### Model Description
|
||||
|
||||
<!-- Provide a longer summary of what this model is. -->
|
||||
|
||||
|
||||
|
||||
- **Developed by:** [More Information Needed]
|
||||
- **Funded by [optional]:** [More Information Needed]
|
||||
- **Shared by [optional]:** [More Information Needed]
|
||||
- **Model type:** [More Information Needed]
|
||||
- **Language(s) (NLP):** [More Information Needed]
|
||||
- **License:** [More Information Needed]
|
||||
- **Finetuned from model [optional]:** [More Information Needed]
|
||||
|
||||
### Model Sources [optional]
|
||||
|
||||
<!-- Provide the basic links for the model. -->
|
||||
|
||||
- **Repository:** [More Information Needed]
|
||||
- **Paper [optional]:** [More Information Needed]
|
||||
- **Demo [optional]:** [More Information Needed]
|
||||
|
||||
## Uses
|
||||
|
||||
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
||||
|
||||
### Direct Use
|
||||
|
||||
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Downstream Use [optional]
|
||||
|
||||
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Out-of-Scope Use
|
||||
|
||||
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Bias, Risks, and Limitations
|
||||
|
||||
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Recommendations
|
||||
|
||||
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
||||
|
||||
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
||||
|
||||
## How to Get Started with the Model
|
||||
|
||||
Use the code below to get started with the model.
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Training Details
|
||||
|
||||
### Training Data
|
||||
|
||||
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Training Procedure
|
||||
|
||||
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
||||
|
||||
#### Preprocessing [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
|
||||
#### Training Hyperparameters
|
||||
|
||||
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
||||
|
||||
#### Speeds, Sizes, Times [optional]
|
||||
|
||||
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Evaluation
|
||||
|
||||
<!-- This section describes the evaluation protocols and provides the results. -->
|
||||
|
||||
### Testing Data, Factors & Metrics
|
||||
|
||||
#### Testing Data
|
||||
|
||||
<!-- This should link to a Dataset Card if possible. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Factors
|
||||
|
||||
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Metrics
|
||||
|
||||
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Results
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Summary
|
||||
|
||||
|
||||
|
||||
## Model Examination [optional]
|
||||
|
||||
<!-- Relevant interpretability work for the model goes here -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Environmental Impact
|
||||
|
||||
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
||||
|
||||
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
||||
|
||||
- **Hardware Type:** [More Information Needed]
|
||||
- **Hours used:** [More Information Needed]
|
||||
- **Cloud Provider:** [More Information Needed]
|
||||
- **Compute Region:** [More Information Needed]
|
||||
- **Carbon Emitted:** [More Information Needed]
|
||||
|
||||
## Technical Specifications [optional]
|
||||
|
||||
### Model Architecture and Objective
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
### Compute Infrastructure
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Hardware
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
#### Software
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Citation [optional]
|
||||
|
||||
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
||||
|
||||
**BibTeX:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
**APA:**
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Glossary [optional]
|
||||
|
||||
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## More Information [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Authors [optional]
|
||||
|
||||
[More Information Needed]
|
||||
|
||||
## Model Card Contact
|
||||
|
||||
[More Information Needed]
|
||||
### Framework versions
|
||||
|
||||
- PEFT 0.19.1
|
||||
48
adapters/sft-lora/checkpoint-90/adapter_config.json
Normal file
48
adapters/sft-lora/checkpoint-90/adapter_config.json
Normal file
@@ -0,0 +1,48 @@
|
||||
{
|
||||
"alora_invocation_tokens": null,
|
||||
"alpha_pattern": {},
|
||||
"arrow_config": null,
|
||||
"auto_mapping": null,
|
||||
"base_model_name_or_path": "Qwen/Qwen3-0.6B",
|
||||
"bias": "none",
|
||||
"corda_config": null,
|
||||
"ensure_weight_tying": false,
|
||||
"eva_config": null,
|
||||
"exclude_modules": null,
|
||||
"fan_in_fan_out": false,
|
||||
"inference_mode": true,
|
||||
"init_lora_weights": true,
|
||||
"layer_replication": null,
|
||||
"layers_pattern": null,
|
||||
"layers_to_transform": null,
|
||||
"loftq_config": {},
|
||||
"lora_alpha": 32,
|
||||
"lora_bias": false,
|
||||
"lora_dropout": 0.05,
|
||||
"lora_ga_config": null,
|
||||
"megatron_config": null,
|
||||
"megatron_core": "megatron.core",
|
||||
"modules_to_save": null,
|
||||
"peft_type": "LORA",
|
||||
"peft_version": "0.19.1",
|
||||
"qalora_group_size": 16,
|
||||
"r": 16,
|
||||
"rank_pattern": {},
|
||||
"revision": null,
|
||||
"target_modules": [
|
||||
"gate_proj",
|
||||
"down_proj",
|
||||
"o_proj",
|
||||
"v_proj",
|
||||
"k_proj",
|
||||
"up_proj",
|
||||
"q_proj"
|
||||
],
|
||||
"target_parameters": null,
|
||||
"task_type": "CAUSAL_LM",
|
||||
"trainable_token_indices": null,
|
||||
"use_bdlora": null,
|
||||
"use_dora": false,
|
||||
"use_qalora": false,
|
||||
"use_rslora": false
|
||||
}
|
||||
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:f9b7aafe23996e555ee3c633855ded62f0d3a41827f7a2947126239a300cca06
|
||||
size 40422168
|
||||
89
adapters/sft-lora/checkpoint-90/chat_template.jinja
Normal file
89
adapters/sft-lora/checkpoint-90/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 %}
|
||||
3
adapters/sft-lora/checkpoint-90/optimizer.pt
Normal file
3
adapters/sft-lora/checkpoint-90/optimizer.pt
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c02077aa2d62c8b071fbdc0157e2ab15d2e8f04fb2ff5bf8bef27f7399f5f873
|
||||
size 81075515
|
||||
3
adapters/sft-lora/checkpoint-90/rng_state.pth
Normal file
3
adapters/sft-lora/checkpoint-90/rng_state.pth
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a29e79e95308c75e7702cb8bb76ee726dec3cc4986dacfcb847c4ad283108edd
|
||||
size 14645
|
||||
3
adapters/sft-lora/checkpoint-90/scheduler.pt
Normal file
3
adapters/sft-lora/checkpoint-90/scheduler.pt
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d8f6b5fec4d818c43b5627862d205d6de3c227cbb6841c5d3cebd3072b69491f
|
||||
size 1465
|
||||
3
adapters/sft-lora/checkpoint-90/tokenizer.json
Normal file
3
adapters/sft-lora/checkpoint-90/tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
|
||||
size 11422650
|
||||
30
adapters/sft-lora/checkpoint-90/tokenizer_config.json
Normal file
30
adapters/sft-lora/checkpoint-90/tokenizer_config.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_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|>"
|
||||
],
|
||||
"is_local": false,
|
||||
"local_files_only": false,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
258
adapters/sft-lora/checkpoint-90/trainer_state.json
Normal file
258
adapters/sft-lora/checkpoint-90/trainer_state.json
Normal file
@@ -0,0 +1,258 @@
|
||||
{
|
||||
"best_global_step": null,
|
||||
"best_metric": null,
|
||||
"best_model_checkpoint": null,
|
||||
"epoch": 2.0,
|
||||
"eval_steps": 20,
|
||||
"global_step": 90,
|
||||
"is_hyper_param_search": false,
|
||||
"is_local_process_zero": true,
|
||||
"is_world_process_zero": true,
|
||||
"log_history": [
|
||||
{
|
||||
"entropy": 0.46982616782188413,
|
||||
"epoch": 0.1111111111111111,
|
||||
"grad_norm": 1.9415351152420044,
|
||||
"learning_rate": 0.00023999999999999998,
|
||||
"loss": 1.166135025024414,
|
||||
"mean_token_accuracy": 0.8076520800590515,
|
||||
"num_tokens": 59002.0,
|
||||
"step": 5
|
||||
},
|
||||
{
|
||||
"entropy": 0.681049507856369,
|
||||
"epoch": 0.2222222222222222,
|
||||
"grad_norm": 0.8071348071098328,
|
||||
"learning_rate": 0.00029929974520764727,
|
||||
"loss": 0.7030046463012696,
|
||||
"mean_token_accuracy": 0.849864411354065,
|
||||
"num_tokens": 120432.0,
|
||||
"step": 10
|
||||
},
|
||||
{
|
||||
"entropy": 0.9322404026985168,
|
||||
"epoch": 0.3333333333333333,
|
||||
"grad_norm": 0.6664227247238159,
|
||||
"learning_rate": 0.0002964661618243908,
|
||||
"loss": 0.878734016418457,
|
||||
"mean_token_accuracy": 0.8135401248931885,
|
||||
"num_tokens": 179678.0,
|
||||
"step": 15
|
||||
},
|
||||
{
|
||||
"entropy": 0.8074370503425599,
|
||||
"epoch": 0.4444444444444444,
|
||||
"grad_norm": 0.6451402306556702,
|
||||
"learning_rate": 0.0002914967719886614,
|
||||
"loss": 0.8701633453369141,
|
||||
"mean_token_accuracy": 0.8204897165298461,
|
||||
"num_tokens": 240600.0,
|
||||
"step": 20
|
||||
},
|
||||
{
|
||||
"epoch": 0.4444444444444444,
|
||||
"eval_entropy": 0.8143169482549032,
|
||||
"eval_loss": 0.924848735332489,
|
||||
"eval_mean_token_accuracy": 0.803371528784434,
|
||||
"eval_num_tokens": 240600.0,
|
||||
"eval_runtime": 1.6201,
|
||||
"eval_samples_per_second": 45.676,
|
||||
"eval_steps_per_second": 1.852,
|
||||
"step": 20
|
||||
},
|
||||
{
|
||||
"entropy": 0.7912694752216339,
|
||||
"epoch": 0.5555555555555556,
|
||||
"grad_norm": 0.4144524037837982,
|
||||
"learning_rate": 0.0002844640405943555,
|
||||
"loss": 0.8696941375732422,
|
||||
"mean_token_accuracy": 0.8263819813728333,
|
||||
"num_tokens": 301638.0,
|
||||
"step": 25
|
||||
},
|
||||
{
|
||||
"entropy": 0.9237359523773193,
|
||||
"epoch": 0.6666666666666666,
|
||||
"grad_norm": 0.5862515568733215,
|
||||
"learning_rate": 0.00027547052070153396,
|
||||
"loss": 0.9361928939819336,
|
||||
"mean_token_accuracy": 0.8028241634368897,
|
||||
"num_tokens": 359243.0,
|
||||
"step": 30
|
||||
},
|
||||
{
|
||||
"entropy": 0.6837044417858124,
|
||||
"epoch": 0.7777777777777778,
|
||||
"grad_norm": 0.4594927728176117,
|
||||
"learning_rate": 0.0002646473580818772,
|
||||
"loss": 0.6992801666259766,
|
||||
"mean_token_accuracy": 0.8513208270072937,
|
||||
"num_tokens": 417098.0,
|
||||
"step": 35
|
||||
},
|
||||
{
|
||||
"entropy": 0.8795680403709412,
|
||||
"epoch": 0.8888888888888888,
|
||||
"grad_norm": 0.5710228681564331,
|
||||
"learning_rate": 0.00025215237881801955,
|
||||
"loss": 0.9085055351257324,
|
||||
"mean_token_accuracy": 0.8098101854324341,
|
||||
"num_tokens": 480008.0,
|
||||
"step": 40
|
||||
},
|
||||
{
|
||||
"epoch": 0.8888888888888888,
|
||||
"eval_entropy": 0.8618650635083517,
|
||||
"eval_loss": 0.9124361872673035,
|
||||
"eval_mean_token_accuracy": 0.8028692404429117,
|
||||
"eval_num_tokens": 480008.0,
|
||||
"eval_runtime": 1.6251,
|
||||
"eval_samples_per_second": 45.535,
|
||||
"eval_steps_per_second": 1.846,
|
||||
"step": 40
|
||||
},
|
||||
{
|
||||
"entropy": 0.8452938675880433,
|
||||
"epoch": 1.0,
|
||||
"grad_norm": 0.789717972278595,
|
||||
"learning_rate": 0.00023816778784387094,
|
||||
"loss": 0.8828925132751465,
|
||||
"mean_token_accuracy": 0.8208261251449585,
|
||||
"num_tokens": 530794.0,
|
||||
"step": 45
|
||||
},
|
||||
{
|
||||
"entropy": 0.5805854141712189,
|
||||
"epoch": 1.1111111111111112,
|
||||
"grad_norm": 0.4138790965080261,
|
||||
"learning_rate": 0.00022289751198639087,
|
||||
"loss": 0.5360542297363281,
|
||||
"mean_token_accuracy": 0.8808212757110596,
|
||||
"num_tokens": 589773.0,
|
||||
"step": 50
|
||||
},
|
||||
{
|
||||
"entropy": 0.8660945177078248,
|
||||
"epoch": 1.2222222222222223,
|
||||
"grad_norm": 0.4917871356010437,
|
||||
"learning_rate": 0.00020656422625324805,
|
||||
"loss": 0.8303131103515625,
|
||||
"mean_token_accuracy": 0.8197528839111328,
|
||||
"num_tokens": 644861.0,
|
||||
"step": 55
|
||||
},
|
||||
{
|
||||
"entropy": 0.5908387929201127,
|
||||
"epoch": 1.3333333333333333,
|
||||
"grad_norm": 0.5149257779121399,
|
||||
"learning_rate": 0.00018940610672978802,
|
||||
"loss": 0.5536936283111572,
|
||||
"mean_token_accuracy": 0.8759726524353028,
|
||||
"num_tokens": 707064.0,
|
||||
"step": 60
|
||||
},
|
||||
{
|
||||
"epoch": 1.3333333333333333,
|
||||
"eval_entropy": 0.7562275131543478,
|
||||
"eval_loss": 0.9295161366462708,
|
||||
"eval_mean_token_accuracy": 0.8002562522888184,
|
||||
"eval_num_tokens": 707064.0,
|
||||
"eval_runtime": 1.6273,
|
||||
"eval_samples_per_second": 45.475,
|
||||
"eval_steps_per_second": 1.844,
|
||||
"step": 60
|
||||
},
|
||||
{
|
||||
"entropy": 0.7860998153686524,
|
||||
"epoch": 1.4444444444444444,
|
||||
"grad_norm": 0.6012740731239319,
|
||||
"learning_rate": 0.00017167335743538317,
|
||||
"loss": 0.7982378482818604,
|
||||
"mean_token_accuracy": 0.8309973835945129,
|
||||
"num_tokens": 763959.0,
|
||||
"step": 65
|
||||
},
|
||||
{
|
||||
"entropy": 0.6057170808315278,
|
||||
"epoch": 1.5555555555555556,
|
||||
"grad_norm": 0.7193827629089355,
|
||||
"learning_rate": 0.00015362456178541982,
|
||||
"loss": 0.6322322368621827,
|
||||
"mean_token_accuracy": 0.8604895114898682,
|
||||
"num_tokens": 826139.0,
|
||||
"step": 70
|
||||
},
|
||||
{
|
||||
"entropy": 0.8781150817871094,
|
||||
"epoch": 1.6666666666666665,
|
||||
"grad_norm": 0.5556202530860901,
|
||||
"learning_rate": 0.00013552291186282273,
|
||||
"loss": 0.8648699760437012,
|
||||
"mean_token_accuracy": 0.8099217295646668,
|
||||
"num_tokens": 883964.0,
|
||||
"step": 75
|
||||
},
|
||||
{
|
||||
"entropy": 0.7820337891578675,
|
||||
"epoch": 1.7777777777777777,
|
||||
"grad_norm": 0.626190721988678,
|
||||
"learning_rate": 0.00011763237048482908,
|
||||
"loss": 0.7500524520874023,
|
||||
"mean_token_accuracy": 0.8313877940177917,
|
||||
"num_tokens": 942825.0,
|
||||
"step": 80
|
||||
},
|
||||
{
|
||||
"epoch": 1.7777777777777777,
|
||||
"eval_entropy": 0.7708820303281149,
|
||||
"eval_loss": 0.9428374767303467,
|
||||
"eval_mean_token_accuracy": 0.7990738352139791,
|
||||
"eval_num_tokens": 942825.0,
|
||||
"eval_runtime": 1.6267,
|
||||
"eval_samples_per_second": 45.49,
|
||||
"eval_steps_per_second": 1.844,
|
||||
"step": 80
|
||||
},
|
||||
{
|
||||
"entropy": 0.6434245944023133,
|
||||
"epoch": 1.8888888888888888,
|
||||
"grad_norm": 0.7037157416343689,
|
||||
"learning_rate": 0.00010021382203072075,
|
||||
"loss": 0.6138159275054932,
|
||||
"mean_token_accuracy": 0.8665528893470764,
|
||||
"num_tokens": 1005474.0,
|
||||
"step": 85
|
||||
},
|
||||
{
|
||||
"entropy": 0.44103629887104034,
|
||||
"epoch": 2.0,
|
||||
"grad_norm": 0.5344287753105164,
|
||||
"learning_rate": 8.352126816011381e-05,
|
||||
"loss": 0.441878604888916,
|
||||
"mean_token_accuracy": 0.9036641597747803,
|
||||
"num_tokens": 1061588.0,
|
||||
"step": 90
|
||||
}
|
||||
],
|
||||
"logging_steps": 5,
|
||||
"max_steps": 135,
|
||||
"num_input_tokens_seen": 0,
|
||||
"num_train_epochs": 3,
|
||||
"save_steps": 500,
|
||||
"stateful_callbacks": {
|
||||
"TrainerControl": {
|
||||
"args": {
|
||||
"should_epoch_stop": false,
|
||||
"should_evaluate": false,
|
||||
"should_log": false,
|
||||
"should_save": true,
|
||||
"should_training_stop": false
|
||||
},
|
||||
"attributes": {}
|
||||
}
|
||||
},
|
||||
"total_flos": 3901053911040000.0,
|
||||
"train_batch_size": 32,
|
||||
"trial_name": null,
|
||||
"trial_params": null
|
||||
}
|
||||
3
adapters/sft-lora/checkpoint-90/training_args.bin
Normal file
3
adapters/sft-lora/checkpoint-90/training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:634fa3e1efca4fb9cf47831d4f352701147dd578361c76a8defa5309a5ed79d4
|
||||
size 5713
|
||||
Reference in New Issue
Block a user