peft safetensors mistral trl sft generated_from_trainer base_model:mistralai/Mistral-7B-Instruct-v0.2 license:apache-2.0 region:us
---
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-3.3.27-Mistral-7b-Multilanguage-3.2.0
  results: []
---

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# ZeroShot-3.3.27-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: 0.0451

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1426        | 0.06  | 100  | 0.1108          |
| 0.1003        | 0.12  | 200  | 0.0847          |
| 0.0986        | 0.19  | 300  | 0.0862          |
| 0.1013        | 0.25  | 400  | 0.0937          |
| 0.0942        | 0.31  | 500  | 0.0942          |
| 0.0963        | 0.37  | 600  | 0.1027          |
| 0.0953        | 0.43  | 700  | 0.0946          |
| 0.0955        | 0.5   | 800  | 0.0849          |
| 0.0909        | 0.56  | 900  | 0.0812          |
| 0.1022        | 0.62  | 1000 | 0.0816          |
| 0.0929        | 0.68  | 1100 | 0.0787          |
| 0.0727        | 0.74  | 1200 | 0.0842          |
| 0.0889        | 0.81  | 1300 | 0.0933          |
| 0.0729        | 0.87  | 1400 | 0.0879          |
| 0.0827        | 0.93  | 1500 | 0.0819          |
| 0.0773        | 0.99  | 1600 | 0.0773          |
| 0.0512        | 1.05  | 1700 | 0.0835          |
| 0.0573        | 1.12  | 1800 | 0.0787          |
| 0.0427        | 1.18  | 1900 | 0.0829          |
| 0.0486        | 1.24  | 2000 | 0.0787          |
| 0.0467        | 1.3   | 2100 | 0.0685          |
| 0.0517        | 1.36  | 2200 | 0.0886          |
| 0.041         | 1.43  | 2300 | 0.0696          |
| 0.0542        | 1.49  | 2400 | 0.0676          |
| 0.0391        | 1.55  | 2500 | 0.0738          |
| 0.0436        | 1.61  | 2600 | 0.0586          |
| 0.0499        | 1.67  | 2700 | 0.0640          |
| 0.0385        | 1.74  | 2800 | 0.0594          |
| 0.0497        | 1.8   | 2900 | 0.0547          |
| 0.0312        | 1.86  | 3000 | 0.0603          |
| 0.039         | 1.92  | 3100 | 0.0479          |
| 0.0328        | 1.98  | 3200 | 0.0459          |
| 0.0202        | 2.05  | 3300 | 0.0521          |
| 0.0125        | 2.11  | 3400 | 0.0517          |
| 0.0085        | 2.17  | 3500 | 0.0472          |
| 0.0056        | 2.23  | 3600 | 0.0556          |
| 0.0183        | 2.29  | 3700 | 0.0495          |
| 0.0081        | 2.36  | 3800 | 0.0506          |
| 0.0079        | 2.42  | 3900 | 0.0526          |
| 0.0069        | 2.48  | 4000 | 0.0451          |
| 0.0081        | 2.54  | 4100 | 0.0459          |
| 0.0115        | 2.6   | 4200 | 0.0451          |
| 0.0067        | 2.67  | 4300 | 0.0464          |
| 0.0052        | 2.73  | 4400 | 0.0469          |
| 0.0127        | 2.79  | 4500 | 0.0459          |
| 0.0097        | 2.85  | 4600 | 0.0457          |
| 0.0113        | 2.91  | 4700 | 0.0456          |
| 0.0123        | 2.98  | 4800 | 0.0455          |


### Framework versions

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