---
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: 0.5616
- Accuracy: 0.5362

## 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
- training_steps: 300

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5245        | 0.07  | 10   | 0.6507          | 0.3355   |
| 0.6666        | 0.13  | 20   | 0.6464          | 0.3816   |
| 0.6527        | 0.2   | 30   | 0.6427          | 0.3684   |
| 0.6168        | 0.27  | 40   | 0.6321          | 0.3980   |
| 0.6584        | 0.33  | 50   | 0.6182          | 0.3914   |
| 0.586         | 0.4   | 60   | 0.6244          | 0.4145   |
| 0.5924        | 0.47  | 70   | 0.6034          | 0.4342   |
| 0.6069        | 0.53  | 80   | 0.6096          | 0.4375   |
| 0.5999        | 0.6   | 90   | 0.6096          | 0.4408   |
| 0.6206        | 0.67  | 100  | 0.6070          | 0.4572   |
| 0.5793        | 0.73  | 110  | 0.6016          | 0.4572   |
| 0.6208        | 0.8   | 120  | 0.5902          | 0.4605   |
| 0.5622        | 0.87  | 130  | 0.5775          | 0.4770   |
| 0.5502        | 0.93  | 140  | 0.5761          | 0.4671   |
| 0.5958        | 1.0   | 150  | 0.5606          | 0.4901   |
| 0.4558        | 1.07  | 160  | 0.5840          | 0.4737   |
| 0.4411        | 1.14  | 170  | 0.5631          | 0.4901   |
| 0.4144        | 1.2   | 180  | 0.5745          | 0.5      |
| 0.4647        | 1.27  | 190  | 0.5932          | 0.4605   |
| 0.4504        | 1.34  | 200  | 0.5799          | 0.5099   |
| 0.4299        | 1.4   | 210  | 0.6488          | 0.4934   |
| 0.425         | 1.47  | 220  | 0.5704          | 0.5132   |
| 0.4152        | 1.54  | 230  | 0.5582          | 0.5066   |
| 0.425         | 1.6   | 240  | 0.5489          | 0.5329   |
| 0.446         | 1.67  | 250  | 0.5479          | 0.5197   |
| 0.3908        | 1.74  | 260  | 0.5564          | 0.5164   |
| 0.443         | 1.8   | 270  | 0.5419          | 0.5033   |
| 0.4081        | 1.87  | 280  | 0.5948          | 0.5066   |
| 0.3944        | 1.94  | 290  | 0.5547          | 0.5395   |
| 0.4005        | 2.0   | 300  | 0.5616          | 0.5362   |


### Framework versions

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