---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- nthakur/miracl-raft-sft-instruct-v0.2
model-index:
- name: Mistral-7B-Instruct-v0.2-miracl-raft-sft-v2.0
  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. -->

# Mistral-7B-Instruct-v0.2-miracl-raft-sft-v2.0

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the nthakur/miracl-raft-sft-instruct-v0.2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2086

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3095        | 0.0987 | 200  | 1.2800          |
| 1.249         | 0.1975 | 400  | 1.2516          |
| 1.2514        | 0.2962 | 600  | 1.2369          |
| 1.275         | 0.3950 | 800  | 1.2263          |
| 1.1984        | 0.4937 | 1000 | 1.2197          |
| 1.1556        | 0.5924 | 1200 | 1.2149          |
| 1.2386        | 0.6912 | 1400 | 1.2116          |
| 1.2661        | 0.7899 | 1600 | 1.2096          |
| 1.2752        | 0.8887 | 1800 | 1.2088          |
| 1.2701        | 0.9874 | 2000 | 1.2086          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1