---
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-3.3.26-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-3.3.26-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: 0.0434

## 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: 2
- 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1164        | 0.06  | 100  | 0.1037          |
| 0.1355        | 0.12  | 200  | 0.1051          |
| 0.1015        | 0.19  | 300  | 0.1142          |
| 0.1026        | 0.25  | 400  | 0.0992          |
| 0.1002        | 0.31  | 500  | 0.1083          |
| 0.0879        | 0.37  | 600  | 0.0894          |
| 0.0778        | 0.43  | 700  | 0.0907          |
| 0.0836        | 0.5   | 800  | 0.0747          |
| 0.0642        | 0.56  | 900  | 0.0645          |
| 0.0496        | 0.62  | 1000 | 0.0709          |
| 0.06          | 0.68  | 1100 | 0.0603          |
| 0.0614        | 0.74  | 1200 | 0.0567          |
| 0.0538        | 0.81  | 1300 | 0.0478          |
| 0.0524        | 0.87  | 1400 | 0.0449          |
| 0.0323        | 0.93  | 1500 | 0.0439          |
| 0.0498        | 0.99  | 1600 | 0.0434          |


### Framework versions

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