Model save
Browse files- README.md +2 -4
- all_results.json +4 -4
- train_results.json +4 -4
- trainer_state.json +37 -9
README.md
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---
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base_model: Qwen/Qwen2.5-3B-Instruct
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datasets: open-r1/verifiable-coding-problems-python
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library_name: transformers
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model_name: Qwen2.5-3B-Open-R1-Code-GRPO
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tags:
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- generated_from_trainer
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- open-r1
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- trl
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- grpo
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licence: license
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# Model Card for Qwen2.5-3B-Open-R1-Code-GRPO
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This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/chenyukang2020-nvidia/huggingface/runs/
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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).
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---
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base_model: Qwen/Qwen2.5-3B-Instruct
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library_name: transformers
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model_name: Qwen2.5-3B-Open-R1-Code-GRPO
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tags:
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- generated_from_trainer
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- trl
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- grpo
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licence: license
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# Model Card for Qwen2.5-3B-Open-R1-Code-GRPO
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This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/chenyukang2020-nvidia/huggingface/runs/oi2qmn1n)
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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).
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all_results.json
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{
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"total_flos": 0.0,
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"train_loss": 1.
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"train_runtime":
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"train_samples": 35735,
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"train_samples_per_second":
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"train_steps_per_second":
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}
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{
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"total_flos": 0.0,
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"train_loss": 1.338229644823614e-07,
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"train_runtime": 85.7242,
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"train_samples": 35735,
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"train_samples_per_second": 2986.32,
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"train_steps_per_second": 5.833
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}
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train_results.json
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{
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"total_flos": 0.0,
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"train_loss": 1.
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"train_runtime":
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"train_samples": 35735,
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"train_samples_per_second":
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"train_steps_per_second":
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}
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{
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"total_flos": 0.0,
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"train_loss": 1.338229644823614e-07,
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"train_runtime": 85.7242,
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"train_samples": 35735,
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"train_samples_per_second": 2986.32,
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"train_steps_per_second": 5.833
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}
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trainer_state.json
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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.
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"eval_steps": 500,
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"global_step":
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"step": 507
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"total_flos": 0.0,
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"train_loss": 1.
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"train_runtime":
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"logging_steps": 1,
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"max_steps": 500,
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"num_input_tokens_seen":
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"save_steps": 50,
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"stateful_callbacks": {
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"step": 507
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