---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: ZeroShot-3.3.24-Mistral-7b-Multilanguage-3.2.0
  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. -->

# ZeroShot-3.3.24-Mistral-7b-Multilanguage-3.2.0

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1109

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1175        | 0.06  | 100  | 0.1109          |
| 0.117         | 0.12  | 200  | 0.1318          |
| 0.1596        | 0.19  | 300  | 0.1316          |
| 0.4487        | 0.25  | 400  | 0.2081          |
| 1.0524        | 0.31  | 500  | 7.3647          |
| 0.0           | 0.37  | 600  | nan             |
| 0.0           | 0.43  | 700  | nan             |
| 0.0           | 0.5   | 800  | nan             |
| 0.0           | 0.56  | 900  | nan             |
| 0.0           | 0.62  | 1000 | nan             |
| 0.0           | 0.68  | 1100 | nan             |
| 0.0           | 0.74  | 1200 | nan             |
| 0.0           | 0.81  | 1300 | nan             |
| 0.0           | 0.87  | 1400 | nan             |
| 0.0           | 0.93  | 1500 | nan             |
| 0.0           | 0.99  | 1600 | nan             |
| 0.0           | 1.05  | 1700 | nan             |
| 0.0           | 1.12  | 1800 | nan             |
| 9.5008        | 1.18  | 1900 | nan             |
| 0.0           | 1.24  | 2000 | nan             |
| 0.0           | 1.3   | 2100 | nan             |
| 0.0           | 1.36  | 2200 | nan             |
| 0.0           | 1.43  | 2300 | nan             |
| 0.0           | 1.49  | 2400 | nan             |
| 0.0           | 1.55  | 2500 | nan             |
| 0.0           | 1.61  | 2600 | nan             |
| 0.0           | 1.67  | 2700 | nan             |
| 0.0           | 1.74  | 2800 | nan             |
| 0.0           | 1.8   | 2900 | nan             |
| 0.0           | 1.86  | 3000 | nan             |
| 0.0           | 1.92  | 3100 | nan             |
| 0.0           | 1.98  | 3200 | nan             |
| 0.0           | 2.05  | 3300 | nan             |
| 0.0           | 2.11  | 3400 | nan             |
| 0.0           | 2.17  | 3500 | nan             |
| 0.0           | 2.23  | 3600 | nan             |
| 0.0           | 2.29  | 3700 | nan             |
| 0.0           | 2.36  | 3800 | nan             |
| 0.0           | 2.42  | 3900 | nan             |
| 0.0           | 2.48  | 4000 | nan             |
| 0.0           | 2.54  | 4100 | nan             |
| 0.0           | 2.6   | 4200 | nan             |
| 0.0           | 2.67  | 4300 | nan             |
| 0.0           | 2.73  | 4400 | nan             |
| 0.0           | 2.79  | 4500 | nan             |
| 0.0           | 2.85  | 4600 | nan             |
| 0.0           | 2.91  | 4700 | nan             |
| 0.0           | 2.98  | 4800 | nan             |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2