---
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_no
  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_no

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: 0.7827
- Accuracy: 0.5493

## 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5293        | 0.07  | 10   | 0.6504          | 0.3520   |
| 0.6652        | 0.13  | 20   | 0.6469          | 0.3783   |
| 0.6523        | 0.2   | 30   | 0.6430          | 0.3651   |
| 0.613         | 0.27  | 40   | 0.6341          | 0.4079   |
| 0.6586        | 0.33  | 50   | 0.6206          | 0.3882   |
| 0.586         | 0.4   | 60   | 0.6269          | 0.4178   |
| 0.594         | 0.47  | 70   | 0.6046          | 0.4276   |
| 0.6063        | 0.53  | 80   | 0.6135          | 0.4178   |
| 0.5988        | 0.6   | 90   | 0.6097          | 0.4276   |
| 0.6217        | 0.67  | 100  | 0.6098          | 0.4539   |
| 0.5817        | 0.73  | 110  | 0.6022          | 0.4539   |
| 0.6219        | 0.8   | 120  | 0.5926          | 0.4572   |
| 0.559         | 0.87  | 130  | 0.5816          | 0.4605   |
| 0.5514        | 0.93  | 140  | 0.5783          | 0.4737   |
| 0.59          | 1.0   | 150  | 0.5622          | 0.4868   |
| 0.46          | 1.07  | 160  | 0.5868          | 0.4803   |
| 0.4484        | 1.14  | 170  | 0.5667          | 0.4868   |
| 0.4162        | 1.2   | 180  | 0.5820          | 0.4803   |
| 0.4716        | 1.27  | 190  | 0.5904          | 0.4638   |
| 0.4486        | 1.34  | 200  | 0.5777          | 0.5099   |
| 0.4264        | 1.4   | 210  | 0.6482          | 0.4967   |
| 0.4236        | 1.47  | 220  | 0.5741          | 0.5033   |
| 0.4141        | 1.54  | 230  | 0.5608          | 0.5164   |
| 0.4308        | 1.6   | 240  | 0.5539          | 0.5099   |
| 0.4505        | 1.67  | 250  | 0.5495          | 0.5033   |
| 0.3958        | 1.74  | 260  | 0.5594          | 0.5099   |
| 0.4432        | 1.8   | 270  | 0.5492          | 0.5164   |
| 0.4067        | 1.87  | 280  | 0.6024          | 0.5066   |
| 0.3988        | 1.94  | 290  | 0.5607          | 0.5099   |
| 0.3992        | 2.0   | 300  | 0.5670          | 0.5164   |
| 0.2304        | 2.07  | 310  | 0.8200          | 0.5362   |
| 0.1696        | 2.14  | 320  | 0.9087          | 0.5296   |
| 0.2255        | 2.2   | 330  | 0.7566          | 0.5362   |
| 0.1923        | 2.27  | 340  | 0.7020          | 0.5197   |
| 0.281         | 2.34  | 350  | 0.6653          | 0.5033   |
| 0.2311        | 2.4   | 360  | 0.6412          | 0.5132   |
| 0.1523        | 2.47  | 370  | 0.8846          | 0.5230   |
| 0.2451        | 2.54  | 380  | 0.9252          | 0.5164   |
| 0.2022        | 2.6   | 390  | 0.7422          | 0.5197   |
| 0.217         | 2.67  | 400  | 0.7558          | 0.5329   |
| 0.165         | 2.74  | 410  | 0.7846          | 0.5428   |
| 0.2025        | 2.8   | 420  | 0.7254          | 0.5230   |
| 0.2201        | 2.87  | 430  | 0.6531          | 0.5296   |
| 0.2037        | 2.94  | 440  | 0.7827          | 0.5493   |


### Framework versions

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