---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- generated_from_trainer
model-index:
- name: Mistral-7B-Instruct-v0.2-absa-MT-restaurants
  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-Instruct-v0.2-absa-MT-restaurants

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0072

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- training_steps: 1200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8237        | 0.13  | 40   | 0.1383          |
| 0.0623        | 0.25  | 80   | 0.0213          |
| 0.0199        | 0.38  | 120  | 0.0176          |
| 0.0178        | 0.5   | 160  | 0.0153          |
| 0.0153        | 0.63  | 200  | 0.0141          |
| 0.0136        | 0.75  | 240  | 0.0127          |
| 0.0111        | 0.88  | 280  | 0.0121          |
| 0.0117        | 1.0   | 320  | 0.0123          |
| 0.0091        | 1.13  | 360  | 0.0117          |
| 0.0102        | 1.25  | 400  | 0.0107          |
| 0.0081        | 1.38  | 440  | 0.0106          |
| 0.0097        | 1.5   | 480  | 0.0100          |
| 0.0091        | 1.63  | 520  | 0.0092          |
| 0.0079        | 1.75  | 560  | 0.0096          |
| 0.0074        | 1.88  | 600  | 0.0089          |
| 0.0075        | 2.0   | 640  | 0.0092          |
| 0.0043        | 2.13  | 680  | 0.0088          |
| 0.0053        | 2.26  | 720  | 0.0092          |
| 0.0047        | 2.38  | 760  | 0.0084          |
| 0.0041        | 2.51  | 800  | 0.0082          |
| 0.005         | 2.63  | 840  | 0.0080          |
| 0.005         | 2.76  | 880  | 0.0072          |
| 0.0045        | 2.88  | 920  | 0.0069          |
| 0.0034        | 3.01  | 960  | 0.0071          |
| 0.0021        | 3.13  | 1000 | 0.0075          |
| 0.0021        | 3.26  | 1040 | 0.0075          |
| 0.0018        | 3.38  | 1080 | 0.0077          |
| 0.0019        | 3.51  | 1120 | 0.0073          |
| 0.0018        | 3.63  | 1160 | 0.0075          |
| 0.0021        | 3.76  | 1200 | 0.0072          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2