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---
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-1_180-samples_config-2_full
  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_task-1_180-samples_config-2_full

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: 1.4892

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.9695        | 0.9412  | 8    | 1.8462          |
| 1.4658        | 2.0     | 17   | 1.3229          |
| 1.0873        | 2.9412  | 25   | 1.0281          |
| 0.8963        | 4.0     | 34   | 0.9578          |
| 0.8173        | 4.9412  | 42   | 0.9242          |
| 0.7207        | 6.0     | 51   | 0.9159          |
| 0.5468        | 6.9412  | 59   | 0.9483          |
| 0.4071        | 8.0     | 68   | 1.0524          |
| 0.2885        | 8.9412  | 76   | 1.2125          |
| 0.2064        | 10.0    | 85   | 1.2909          |
| 0.1585        | 10.9412 | 93   | 1.3461          |
| 0.125         | 12.0    | 102  | 1.3770          |
| 0.1121        | 12.9412 | 110  | 1.4892          |


### Framework versions

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