---
base_model: mistralai/Mistral-7B-Instruct-v0.3
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-2_120-samples_config-2_full_auto
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B_task-2_120-samples_config-2_full_auto

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9351

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- 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: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.1522        | 0.9091  | 5    | 1.0969          |
| 1.0455        | 2.0     | 11   | 0.9818          |
| 0.9291        | 2.9091  | 16   | 0.9178          |
| 0.8133        | 4.0     | 22   | 0.8174          |
| 0.754         | 4.9091  | 27   | 0.7907          |
| 0.7232        | 6.0     | 33   | 0.7768          |
| 0.7137        | 6.9091  | 38   | 0.7700          |
| 0.6783        | 8.0     | 44   | 0.7681          |
| 0.6309        | 8.9091  | 49   | 0.7697          |
| 0.6237        | 10.0    | 55   | 0.7780          |
| 0.5633        | 10.9091 | 60   | 0.7931          |
| 0.4943        | 12.0    | 66   | 0.8165          |
| 0.4499        | 12.9091 | 71   | 0.8476          |
| 0.4037        | 14.0    | 77   | 0.9135          |
| 0.3067        | 14.9091 | 82   | 0.9351          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1