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--- |
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library_name: peft |
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license: other |
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base_model: Qwen/Qwen2.5-32B-Instruct |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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model-index: |
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- name: MATH_training_QwQ_32B_Preview |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# MATH_training_QwQ_32B_Preview |
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This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the MATH_training_Qwen_QwQ_32B_Preview dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1193 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 4 |
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- total_eval_batch_size: 4 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.2322 | 0.1564 | 200 | 0.2143 | |
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| 0.1419 | 0.3127 | 400 | 0.1674 | |
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| 0.1137 | 0.4691 | 600 | 0.1510 | |
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| 0.1457 | 0.6255 | 800 | 0.1406 | |
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| 0.0953 | 0.7819 | 1000 | 0.1333 | |
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| 0.1201 | 0.9382 | 1200 | 0.1268 | |
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| 0.0899 | 1.0946 | 1400 | 0.1289 | |
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| 0.0548 | 1.2510 | 1600 | 0.1269 | |
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| 0.0323 | 1.4073 | 1800 | 0.1240 | |
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| 0.0414 | 1.5637 | 2000 | 0.1207 | |
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| 0.0375 | 1.7201 | 2200 | 0.1202 | |
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| 0.0512 | 1.8765 | 2400 | 0.1201 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.46.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
