---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- mbe
metrics:
- accuracy
model-index:
- name: Mistral-7B-v0.1_mbe_positive
  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. -->

# Mistral-7B-v0.1_mbe_positive

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the mbe dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0233
- Accuracy: 0.6809

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3217        | 0.07  | 10   | 0.7263          | 0.4901   |
| 0.56          | 0.13  | 20   | 0.6898          | 0.5526   |
| 0.5281        | 0.2   | 30   | 0.6465          | 0.5888   |
| 0.994         | 0.27  | 40   | 0.7351          | 0.5987   |
| 0.4785        | 0.33  | 50   | 0.6004          | 0.6118   |
| 0.4732        | 0.4   | 60   | 0.5783          | 0.6349   |
| 0.4466        | 0.47  | 70   | 0.5714          | 0.6414   |
| 0.8737        | 0.53  | 80   | 0.5673          | 0.6184   |
| 0.4471        | 0.6   | 90   | 0.5631          | 0.6283   |
| 0.46          | 0.67  | 100  | 0.5504          | 0.6349   |
| 0.3294        | 0.73  | 110  | 0.6010          | 0.625    |
| 0.6526        | 0.8   | 120  | 0.5731          | 0.6283   |
| 0.3712        | 0.87  | 130  | 0.5379          | 0.6447   |
| 0.3341        | 0.93  | 140  | 0.5409          | 0.6283   |
| 0.552         | 1.0   | 150  | 0.5311          | 0.6382   |
| 0.4681        | 1.07  | 160  | 0.5371          | 0.6414   |
| 0.3119        | 1.14  | 170  | 0.6172          | 0.6283   |
| 0.3082        | 1.2   | 180  | 0.5361          | 0.6513   |
| 0.5217        | 1.27  | 190  | 0.5468          | 0.625    |
| 0.3888        | 1.34  | 200  | 0.5891          | 0.6316   |
| 0.2841        | 1.4   | 210  | 0.5429          | 0.6283   |
| 0.2728        | 1.47  | 220  | 0.5247          | 0.6382   |
| 0.5563        | 1.54  | 230  | 0.5004          | 0.6513   |
| 0.2862        | 1.6   | 240  | 0.4741          | 0.6546   |
| 0.2289        | 1.67  | 250  | 0.5441          | 0.6513   |
| 0.2481        | 1.74  | 260  | 0.5171          | 0.6513   |
| 0.329         | 1.8   | 270  | 0.5371          | 0.6546   |
| 0.1741        | 1.87  | 280  | 0.5412          | 0.6678   |
| 0.2888        | 1.94  | 290  | 0.5131          | 0.6711   |
| 0.4157        | 2.0   | 300  | 0.4555          | 0.6447   |
| 0.1982        | 2.07  | 310  | 0.5670          | 0.6612   |
| 0.106         | 2.14  | 320  | 0.7943          | 0.6678   |
| 0.1718        | 2.2   | 330  | 0.7496          | 0.6645   |
| 0.214         | 2.27  | 340  | 0.6264          | 0.6842   |
| 0.1571        | 2.34  | 350  | 0.6139          | 0.6316   |
| 0.1432        | 2.4   | 360  | 0.6199          | 0.6842   |
| 0.1038        | 2.47  | 370  | 0.6368          | 0.6974   |
| 0.1728        | 2.54  | 380  | 0.7889          | 0.6678   |
| 0.14          | 2.6   | 390  | 0.7952          | 0.6546   |
| 0.1522        | 2.67  | 400  | 0.7745          | 0.6579   |
| 0.1345        | 2.74  | 410  | 0.7231          | 0.6513   |
| 0.1587        | 2.8   | 420  | 0.7154          | 0.6480   |
| 0.1391        | 2.87  | 430  | 0.6923          | 0.6513   |
| 0.129         | 2.94  | 440  | 0.6484          | 0.6711   |
| 0.2092        | 3.01  | 450  | 0.5822          | 0.6743   |
| 0.015         | 3.07  | 460  | 1.1217          | 0.6579   |
| 0.051         | 3.14  | 470  | 1.5790          | 0.6480   |
| 0.0999        | 3.21  | 480  | 1.5168          | 0.6678   |
| 0.1776        | 3.27  | 490  | 1.2342          | 0.6875   |
| 0.0612        | 3.34  | 500  | 1.0371          | 0.6974   |
| 0.0858        | 3.41  | 510  | 1.0277          | 0.6776   |
| 0.0316        | 3.47  | 520  | 1.0387          | 0.6809   |
| 0.1899        | 3.54  | 530  | 0.8185          | 0.6908   |
| 0.1517        | 3.61  | 540  | 0.7054          | 0.6842   |
| 0.0324        | 3.67  | 550  | 0.8505          | 0.6842   |
| 0.0646        | 3.74  | 560  | 1.0057          | 0.6612   |
| 0.1038        | 3.81  | 570  | 1.0027          | 0.6645   |
| 0.0844        | 3.87  | 580  | 0.9926          | 0.6513   |
| 0.0986        | 3.94  | 590  | 0.9246          | 0.6579   |
| 0.0627        | 4.01  | 600  | 0.8539          | 0.6546   |
| 0.0513        | 4.07  | 610  | 0.9247          | 0.6513   |
| 0.0484        | 4.14  | 620  | 1.1128          | 0.6546   |
| 0.0244        | 4.21  | 630  | 1.2702          | 0.6480   |
| 0.0672        | 4.27  | 640  | 1.7169          | 0.6414   |
| 0.0824        | 4.34  | 650  | 1.6627          | 0.6414   |
| 0.0068        | 4.41  | 660  | 1.3425          | 0.6349   |
| 0.044         | 4.47  | 670  | 1.2208          | 0.6612   |
| 0.0378        | 4.54  | 680  | 1.2891          | 0.6447   |
| 0.0411        | 4.61  | 690  | 1.3528          | 0.6612   |
| 0.0215        | 4.67  | 700  | 1.2606          | 0.6678   |
| 0.0438        | 4.74  | 710  | 1.2515          | 0.6546   |
| 0.0936        | 4.81  | 720  | 1.0858          | 0.6645   |
| 0.0305        | 4.87  | 730  | 0.9839          | 0.6579   |
| 0.0282        | 4.94  | 740  | 1.0233          | 0.6809   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1