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---
library_name: peft
base_model: peiyi9979/math-shepherd-mistral-7b-prm
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: v4_mistral_lora
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. -->
# v4_mistral_lora
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.
It achieves the following results on the evaluation set:
- Loss: 0.2886
- Accuracy: 0.8631
- Precision: 0.8457
- Recall: 0.6260
- F1: 0.7195
## 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: 2e-05
- train_batch_size: 6
- eval_batch_size: 8
- seed: 89234
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 3
- total_train_batch_size: 72
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 0 | 0 | 0.5995 | 0.7340 | 0.6 | 0.1535 | 0.2445 |
| 0.7266 | 0.0251 | 20 | 0.5909 | 0.7384 | 0.6232 | 0.1693 | 0.2663 |
| 0.674 | 0.0502 | 40 | 0.5497 | 0.7517 | 0.6526 | 0.2441 | 0.3553 |
| 0.5187 | 0.0753 | 60 | 0.4896 | 0.7759 | 0.6409 | 0.4567 | 0.5333 |
| 0.4811 | 0.1004 | 80 | 0.4410 | 0.7958 | 0.7066 | 0.4646 | 0.5606 |
| 0.2811 | 0.1255 | 100 | 0.4249 | 0.8102 | 0.7595 | 0.4724 | 0.5825 |
| 0.2959 | 0.1506 | 120 | 0.3751 | 0.8212 | 0.7674 | 0.5197 | 0.6197 |
| 0.336 | 0.1757 | 140 | 0.3764 | 0.8278 | 0.8451 | 0.4724 | 0.6061 |
| 0.3239 | 0.2008 | 160 | 0.3608 | 0.8201 | 0.8421 | 0.4409 | 0.5788 |
| 0.2767 | 0.2259 | 180 | 0.3362 | 0.8543 | 0.8112 | 0.6260 | 0.7067 |
| 0.276 | 0.2510 | 200 | 0.3406 | 0.8389 | 0.8462 | 0.5197 | 0.6439 |
| 0.2715 | 0.2762 | 220 | 0.3223 | 0.8411 | 0.8274 | 0.5472 | 0.6588 |
| 0.2737 | 0.3013 | 240 | 0.3202 | 0.8521 | 0.8125 | 0.6142 | 0.6996 |
| 0.3245 | 0.3264 | 260 | 0.3098 | 0.8466 | 0.8249 | 0.5748 | 0.6775 |
| 0.2868 | 0.3515 | 280 | 0.3159 | 0.8433 | 0.7887 | 0.6024 | 0.6830 |
| 0.2601 | 0.3766 | 300 | 0.3105 | 0.8587 | 0.7669 | 0.7126 | 0.7388 |
| 0.2597 | 0.4017 | 320 | 0.3162 | 0.8510 | 0.8362 | 0.5827 | 0.6868 |
| 0.287 | 0.4268 | 340 | 0.2997 | 0.8532 | 0.8071 | 0.6260 | 0.7051 |
| 0.3115 | 0.4519 | 360 | 0.3028 | 0.8543 | 0.8315 | 0.6024 | 0.6986 |
| 0.2654 | 0.4770 | 380 | 0.3008 | 0.8543 | 0.8245 | 0.6102 | 0.7014 |
| 0.2443 | 0.5021 | 400 | 0.2955 | 0.8565 | 0.8039 | 0.6457 | 0.7162 |
| 0.2743 | 0.5272 | 420 | 0.3011 | 0.8543 | 0.8389 | 0.5945 | 0.6959 |
| 0.2248 | 0.5523 | 440 | 0.3031 | 0.8532 | 0.8380 | 0.5906 | 0.6928 |
| 0.2149 | 0.5774 | 460 | 0.2868 | 0.8609 | 0.7991 | 0.6732 | 0.7308 |
| 0.1998 | 0.6025 | 480 | 0.2975 | 0.8587 | 0.8316 | 0.6220 | 0.7117 |
| 0.2459 | 0.6276 | 500 | 0.2978 | 0.8510 | 0.8324 | 0.5866 | 0.6882 |
| 0.1953 | 0.6527 | 520 | 0.2989 | 0.8576 | 0.8492 | 0.5984 | 0.7021 |
| 0.3153 | 0.6778 | 540 | 0.2864 | 0.8642 | 0.8359 | 0.6417 | 0.7261 |
| 0.2172 | 0.7029 | 560 | 0.3190 | 0.8444 | 0.8844 | 0.5118 | 0.6484 |
| 0.2604 | 0.7280 | 580 | 0.2830 | 0.8687 | 0.8358 | 0.6614 | 0.7385 |
| 0.2671 | 0.7531 | 600 | 0.2970 | 0.8565 | 0.8523 | 0.5906 | 0.6977 |
| 0.2049 | 0.7782 | 620 | 0.2862 | 0.8587 | 0.8316 | 0.6220 | 0.7117 |
| 0.2972 | 0.8033 | 640 | 0.2890 | 0.8609 | 0.8404 | 0.6220 | 0.7149 |
| 0.1953 | 0.8285 | 660 | 0.2911 | 0.8609 | 0.8441 | 0.6181 | 0.7136 |
| 0.24 | 0.8536 | 680 | 0.2824 | 0.8653 | 0.8367 | 0.6457 | 0.7289 |
| 0.282 | 0.8787 | 700 | 0.2860 | 0.8631 | 0.8385 | 0.6339 | 0.7220 |
| 0.1931 | 0.9038 | 720 | 0.2885 | 0.8620 | 0.8413 | 0.6260 | 0.7178 |
| 0.2251 | 0.9289 | 740 | 0.2898 | 0.8631 | 0.8457 | 0.6260 | 0.7195 |
| 0.178 | 0.9540 | 760 | 0.2889 | 0.8631 | 0.8457 | 0.6260 | 0.7195 |
| 0.2431 | 0.9791 | 780 | 0.2886 | 0.8631 | 0.8457 | 0.6260 | 0.7195 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |