---
library_name: peft
base_model: peiyi9979/math-shepherd-mistral-7b-prm
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: v3_mistral_balance1_base_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. -->

# v3_mistral_balance1_base_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: 0.0134
- Accuracy: 0.9975
- Precision: 0.9643
- Recall: 0.9474
- F1: 0.9558

## 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: 8
- eval_batch_size: 8
- seed: 8569382
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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    | 0.3256          | 0.9369   | 0.1429    | 0.2456 | 0.1806 |
| 0.4498        | 0.0258 | 20   | 0.2868          | 0.9474   | 0.1449    | 0.1754 | 0.1587 |
| 0.242         | 0.0515 | 40   | 0.1434          | 0.9672   | 0.2       | 0.0526 | 0.0833 |
| 0.1628        | 0.0773 | 60   | 0.1080          | 0.9692   | 0.3810    | 0.1404 | 0.2051 |
| 0.1241        | 0.1031 | 80   | 0.0874          | 0.9707   | 0.475     | 0.3333 | 0.3918 |
| 0.0676        | 0.1289 | 100  | 0.0690          | 0.9692   | 0.4713    | 0.7193 | 0.5694 |
| 0.03          | 0.1546 | 120  | 0.0472          | 0.9821   | 0.6296    | 0.8947 | 0.7391 |
| 0.0109        | 0.1804 | 140  | 0.0341          | 0.9911   | 0.8305    | 0.8596 | 0.8448 |
| 0.043         | 0.2062 | 160  | 0.0337          | 0.9916   | 0.8333    | 0.8772 | 0.8547 |
| 0.0233        | 0.2320 | 180  | 0.0272          | 0.9926   | 0.8281    | 0.9298 | 0.8760 |
| 0.029         | 0.2577 | 200  | 0.0233          | 0.9921   | 0.8254    | 0.9123 | 0.8667 |
| 0.0138        | 0.2835 | 220  | 0.0210          | 0.9930   | 0.8413    | 0.9298 | 0.8833 |
| 0.0141        | 0.3093 | 240  | 0.0175          | 0.9955   | 0.9286    | 0.9123 | 0.9204 |
| 0.0037        | 0.3351 | 260  | 0.0170          | 0.9940   | 0.8814    | 0.9123 | 0.8966 |
| 0.0076        | 0.3608 | 280  | 0.0186          | 0.9955   | 0.9       | 0.9474 | 0.9231 |
| 0.0133        | 0.3866 | 300  | 0.0152          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0084        | 0.4124 | 320  | 0.0164          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0039        | 0.4381 | 340  | 0.0141          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0102        | 0.4639 | 360  | 0.0138          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0019        | 0.4897 | 380  | 0.0152          | 0.9965   | 0.9310    | 0.9474 | 0.9391 |
| 0.0007        | 0.5155 | 400  | 0.0145          | 0.9970   | 0.9636    | 0.9298 | 0.9464 |
| 0.0028        | 0.5412 | 420  | 0.0141          | 0.9965   | 0.9310    | 0.9474 | 0.9391 |
| 0.0035        | 0.5670 | 440  | 0.0147          | 0.9960   | 0.9623    | 0.8947 | 0.9273 |
| 0.0016        | 0.5928 | 460  | 0.0159          | 0.9965   | 0.9808    | 0.8947 | 0.9358 |
| 0.0262        | 0.6186 | 480  | 0.0141          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0294        | 0.6443 | 500  | 0.0165          | 0.9970   | 0.9811    | 0.9123 | 0.9455 |
| 0.0054        | 0.6701 | 520  | 0.0145          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0293        | 0.6959 | 540  | 0.0148          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0133        | 0.7216 | 560  | 0.0137          | 0.9970   | 0.9474    | 0.9474 | 0.9474 |
| 0.0028        | 0.7474 | 580  | 0.0141          | 0.9980   | 0.9818    | 0.9474 | 0.9643 |
| 0.0012        | 0.7732 | 600  | 0.0142          | 0.9980   | 0.9818    | 0.9474 | 0.9643 |
| 0.0018        | 0.7990 | 620  | 0.0136          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0164        | 0.8247 | 640  | 0.0140          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0359        | 0.8505 | 660  | 0.0143          | 0.9980   | 0.9818    | 0.9474 | 0.9643 |
| 0.0038        | 0.8763 | 680  | 0.0137          | 0.9980   | 0.9818    | 0.9474 | 0.9643 |
| 0.011         | 0.9021 | 700  | 0.0134          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0144        | 0.9278 | 720  | 0.0134          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |
| 0.0284        | 0.9536 | 740  | 0.0134          | 0.9980   | 0.9818    | 0.9474 | 0.9643 |
| 0.0066        | 0.9794 | 760  | 0.0134          | 0.9975   | 0.9643    | 0.9474 | 0.9558 |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3