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Model: laion/alfworld-swesmith-r2egym-swegym-131k-32B-lc
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2026-05-04 07:27:43 +08:00
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---
library_name: transformers
license: other
base_model: Qwen/Qwen3-32B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: sft__glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k-glm46-swesmith-maxeps-131k-GLM-4-7
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sft__glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k-glm46-swesmith-maxeps-131k-GLM-4-7
This model is a fine-tuned version of [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) on the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--glm46-neulab-agenttuning-alfworld-sandboxes-maxeps-131k/snapshots/fdb0d0afe08aa3c31c7605b40c18d5e48fdc206c_thinking_preprocessed, the /e/data1/datasets/playground/ot/hf_hub/datasets--penfever--glm46-swesmith-maxeps-131k/snapshots/4d4c2d4a9d21f73870ed31c7bc6028035b3b6ca7_thinking_preprocessed, the /e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent2--GLM-4.7-r2egym_sandboxes-maxeps-131k/snapshots/167ff86e8203fa2412574480bf52623cb62320e8_thinking_preprocessed and the /e/data1/datasets/playground/ot/hf_hub/datasets--DCAgent2--glm46-swegym-tasks-maxeps-131k/snapshots/bc7a253d567261d84db295a138b8af86eac6ae4c_thinking_preprocessed datasets.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- gradient_accumulation_steps: 6
- total_train_batch_size: 384
- total_eval_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7.0
### Training results
### Framework versions
- Transformers 4.57.6
- Pytorch 2.9.1+cu130
- Datasets 4.7.0
- Tokenizers 0.22.2

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{
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"<think>": 151667,
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{
"achieved_tflops_per_gpu": 1063.315854388195,
"achieved_tflops_per_gpu_theoretical": 121285192.64972909,
"epoch": 6.597039473684211,
"loss_nan_ranks": 0,
"loss_rank_avg": 0.18427793681621552,
"mfu_percent": 75.14599677655089,
"mfu_percent_theoretical": 8571391.706694635,
"total_flos": 7.249602429950362e+16,
"train_loss": 0.0,
"train_runtime": 1.0653,
"train_samples_per_second": 7990.221,
"train_steps_per_second": 1333.894
}

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{%- 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 %}

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"model_type": "qwen3",
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"num_hidden_layers": 64,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000,
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"transformers_version": "4.57.6",
"use_cache": false,
"use_sliding_window": false,
"vocab_size": 151936
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"do_sample": true,
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"pad_token_id": 151643,
"temperature": 0.6,
"top_k": 20,
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