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--- |
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library_name: peft |
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base_model: peiyi9979/math-shepherd-mistral-7b-prm |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: v3c_mistral_lora_lastn |
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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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# v3c_mistral_lora_lastn |
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This model is a fine-tuned version of [peiyi9979/math-shepherd-mistral-7b-prm](https://huggingface.co/peiyi9979/math-shepherd-mistral-7b-prm) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3067 |
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- Accuracy: 0.8592 |
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- Precision: 0.8580 |
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- Recall: 0.5968 |
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- F1: 0.7040 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 765837 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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- optimizer: Use OptimizerNames.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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0 | 0 | 0.6026 | 0.7339 | 0.6 | 0.1542 | 0.2453 | |
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| 0.5522 | 0.0495 | 20 | 0.5768 | 0.7395 | 0.5682 | 0.2964 | 0.3896 | |
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| 0.4818 | 0.0990 | 40 | 0.4859 | 0.7761 | 0.6835 | 0.3755 | 0.4847 | |
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| 0.3892 | 0.1485 | 60 | 0.4218 | 0.7982 | 0.6766 | 0.5375 | 0.5991 | |
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| 0.2916 | 0.1980 | 80 | 0.3747 | 0.8237 | 0.7701 | 0.5296 | 0.6276 | |
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| 0.2191 | 0.2475 | 100 | 0.3538 | 0.8304 | 0.7778 | 0.5534 | 0.6467 | |
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| 0.2189 | 0.2970 | 120 | 0.3754 | 0.8248 | 0.88 | 0.4348 | 0.5820 | |
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| 0.1841 | 0.3465 | 140 | 0.3427 | 0.8415 | 0.8438 | 0.5336 | 0.6538 | |
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| 0.2144 | 0.3960 | 160 | 0.3301 | 0.8404 | 0.8303 | 0.5415 | 0.6555 | |
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| 0.2638 | 0.4455 | 180 | 0.3202 | 0.8470 | 0.8485 | 0.5534 | 0.6699 | |
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| 0.2032 | 0.4950 | 200 | 0.3125 | 0.8570 | 0.8370 | 0.6087 | 0.7048 | |
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| 0.1703 | 0.5446 | 220 | 0.3295 | 0.8337 | 0.8552 | 0.4901 | 0.6231 | |
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| 0.175 | 0.5941 | 240 | 0.3116 | 0.8503 | 0.8471 | 0.5692 | 0.6809 | |
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| 0.1927 | 0.6436 | 260 | 0.3218 | 0.8459 | 0.8654 | 0.5336 | 0.6601 | |
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| 0.1848 | 0.6931 | 280 | 0.3069 | 0.8647 | 0.8659 | 0.6126 | 0.7176 | |
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| 0.222 | 0.7426 | 300 | 0.3036 | 0.8581 | 0.8613 | 0.5889 | 0.6995 | |
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| 0.1693 | 0.7921 | 320 | 0.3096 | 0.8525 | 0.8614 | 0.5652 | 0.6826 | |
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| 0.1752 | 0.8416 | 340 | 0.3108 | 0.8503 | 0.8554 | 0.5613 | 0.6778 | |
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| 0.2353 | 0.8911 | 360 | 0.3072 | 0.8592 | 0.8580 | 0.5968 | 0.7040 | |
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| 0.1984 | 0.9406 | 380 | 0.3078 | 0.8603 | 0.8629 | 0.5968 | 0.7056 | |
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| 0.2194 | 0.9901 | 400 | 0.3067 | 0.8592 | 0.8580 | 0.5968 | 0.7040 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.0 |
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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 |
