---
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-3.3.25-Mistral-7b-Multilanguage-3.2.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ZeroShot-3.3.25-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: 0.0503

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1409        | 0.06  | 100  | 0.0993          |
| 0.0916        | 0.12  | 200  | 0.0877          |
| 0.0965        | 0.19  | 300  | 0.0970          |
| 0.0933        | 0.25  | 400  | 0.0898          |
| 0.0776        | 0.31  | 500  | 0.0749          |
| 0.0793        | 0.37  | 600  | 0.0850          |
| 0.0768        | 0.43  | 700  | 0.0701          |
| 0.0597        | 0.5   | 800  | 0.0767          |
| 0.0648        | 0.56  | 900  | 0.0766          |
| 0.0635        | 0.62  | 1000 | 0.0649          |
| 0.0536        | 0.68  | 1100 | 0.0641          |
| 0.0511        | 0.74  | 1200 | 0.0559          |
| 0.0638        | 0.81  | 1300 | 0.0507          |
| 0.0462        | 0.87  | 1400 | 0.0512          |
| 0.0494        | 0.93  | 1500 | 0.0507          |
| 0.0457        | 0.99  | 1600 | 0.0503          |


### Framework versions

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