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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: 0.2841
- Accuracy: 0.8687
- Precision: 0.8392
- Recall: 0.6575
- F1: 0.7373
## 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 |
| 0.6057 | 0.0254 | 20 | 0.5918 | 0.7373 | 0.625 | 0.1575 | 0.2516 |
| 0.5356 | 0.0507 | 40 | 0.5521 | 0.7517 | 0.6790 | 0.2165 | 0.3284 |
| 0.5141 | 0.0761 | 60 | 0.5021 | 0.7627 | 0.5890 | 0.5079 | 0.5455 |
| 0.3594 | 0.1015 | 80 | 0.4427 | 0.7980 | 0.7448 | 0.4252 | 0.5414 |
| 0.3988 | 0.1268 | 100 | 0.4067 | 0.8245 | 0.7684 | 0.5354 | 0.6311 |
| 0.3205 | 0.1522 | 120 | 0.3738 | 0.8201 | 0.8138 | 0.4646 | 0.5915 |
| 0.3026 | 0.1776 | 140 | 0.3680 | 0.8289 | 0.8235 | 0.4961 | 0.6192 |
| 0.2886 | 0.2030 | 160 | 0.3467 | 0.8433 | 0.8590 | 0.5276 | 0.6537 |
| 0.2345 | 0.2283 | 180 | 0.3289 | 0.8587 | 0.7972 | 0.6654 | 0.7253 |
| 0.2964 | 0.2537 | 200 | 0.3322 | 0.8377 | 0.8497 | 0.5118 | 0.6388 |
| 0.2655 | 0.2791 | 220 | 0.3495 | 0.8278 | 0.8657 | 0.4567 | 0.5979 |
| 0.3252 | 0.3044 | 240 | 0.3189 | 0.8455 | 0.8314 | 0.5630 | 0.6714 |
| 0.2561 | 0.3298 | 260 | 0.3228 | 0.8532 | 0.8201 | 0.6102 | 0.6998 |
| 0.1661 | 0.3552 | 280 | 0.3141 | 0.8499 | 0.8598 | 0.5551 | 0.6746 |
| 0.1812 | 0.3805 | 300 | 0.3330 | 0.8300 | 0.8378 | 0.4882 | 0.6169 |
| 0.3265 | 0.4059 | 320 | 0.2961 | 0.8543 | 0.8280 | 0.6063 | 0.7 |
| 0.2217 | 0.4313 | 340 | 0.2970 | 0.8664 | 0.8065 | 0.6890 | 0.7431 |
| 0.2058 | 0.4567 | 360 | 0.3054 | 0.8521 | 0.8333 | 0.5906 | 0.6912 |
| 0.225 | 0.4820 | 380 | 0.3018 | 0.8576 | 0.8531 | 0.5945 | 0.7007 |
| 0.2045 | 0.5074 | 400 | 0.3174 | 0.8510 | 0.8742 | 0.5472 | 0.6731 |
| 0.2368 | 0.5328 | 420 | 0.3156 | 0.8477 | 0.8537 | 0.5512 | 0.6699 |
| 0.2162 | 0.5581 | 440 | 0.2928 | 0.8609 | 0.8441 | 0.6181 | 0.7136 |
| 0.1664 | 0.5835 | 460 | 0.2978 | 0.8598 | 0.8325 | 0.6260 | 0.7146 |
| 0.2282 | 0.6089 | 480 | 0.3031 | 0.8587 | 0.8539 | 0.5984 | 0.7037 |
| 0.1983 | 0.6342 | 500 | 0.2958 | 0.8543 | 0.8177 | 0.6181 | 0.7040 |
| 0.1843 | 0.6596 | 520 | 0.3055 | 0.8609 | 0.8556 | 0.6063 | 0.7097 |
| 0.1915 | 0.6850 | 540 | 0.2818 | 0.8675 | 0.8160 | 0.6811 | 0.7425 |
| 0.1582 | 0.7104 | 560 | 0.2887 | 0.8675 | 0.8641 | 0.6260 | 0.7260 |
| 0.2003 | 0.7357 | 580 | 0.2872 | 0.8653 | 0.8511 | 0.6299 | 0.7240 |
| 0.2345 | 0.7611 | 600 | 0.2827 | 0.8687 | 0.8293 | 0.6693 | 0.7407 |
| 0.2107 | 0.7865 | 620 | 0.2954 | 0.8642 | 0.8701 | 0.6063 | 0.7146 |
| 0.2562 | 0.8118 | 640 | 0.2938 | 0.8642 | 0.8503 | 0.6260 | 0.7211 |
| 0.1054 | 0.8372 | 660 | 0.2917 | 0.8642 | 0.8503 | 0.6260 | 0.7211 |
| 0.2837 | 0.8626 | 680 | 0.2842 | 0.8664 | 0.8376 | 0.6496 | 0.7317 |
| 0.1779 | 0.8879 | 700 | 0.2841 | 0.8709 | 0.8477 | 0.6575 | 0.7406 |
| 0.2277 | 0.9133 | 720 | 0.2847 | 0.8675 | 0.8384 | 0.6535 | 0.7345 |
| 0.2099 | 0.9387 | 740 | 0.2828 | 0.8720 | 0.8485 | 0.6614 | 0.7434 |
| 0.2167 | 0.9641 | 760 | 0.2835 | 0.8709 | 0.8477 | 0.6575 | 0.7406 |
| 0.1901 | 0.9894 | 780 | 0.2841 | 0.8687 | 0.8392 | 0.6575 | 0.7373 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3 |