---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9724

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.03
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0248        | 0.03  | 50   | 1.0145          |
| 1.0168        | 0.06  | 100  | 1.0078          |
| 1.008         | 0.09  | 150  | 1.0058          |
| 1.0082        | 0.12  | 200  | 1.0030          |
| 0.9846        | 0.14  | 250  | 1.0005          |
| 0.9807        | 0.17  | 300  | 0.9998          |
| 0.9968        | 0.2   | 350  | 0.9992          |
| 0.9834        | 0.23  | 400  | 0.9967          |
| 1.0267        | 0.26  | 450  | 0.9953          |
| 1.0119        | 0.29  | 500  | 0.9937          |
| 0.9759        | 0.32  | 550  | 0.9939          |
| 0.9978        | 0.35  | 600  | 0.9921          |
| 1.0145        | 0.38  | 650  | 0.9901          |
| 1.0064        | 0.4   | 700  | 0.9897          |
| 0.9949        | 0.43  | 750  | 0.9890          |
| 0.9936        | 0.46  | 800  | 0.9865          |
| 0.9944        | 0.49  | 850  | 0.9852          |
| 0.9819        | 0.52  | 900  | 0.9845          |
| 0.9991        | 0.55  | 950  | 0.9826          |
| 0.9874        | 0.58  | 1000 | 0.9812          |
| 0.981         | 0.61  | 1050 | 0.9798          |
| 0.9807        | 0.64  | 1100 | 0.9789          |
| 0.9639        | 0.67  | 1150 | 0.9776          |
| 0.9645        | 0.69  | 1200 | 0.9767          |
| 0.9788        | 0.72  | 1250 | 0.9758          |
| 0.9823        | 0.75  | 1300 | 0.9751          |
| 0.9906        | 0.78  | 1350 | 0.9745          |
| 0.9536        | 0.81  | 1400 | 0.9738          |
| 0.9635        | 0.84  | 1450 | 0.9732          |
| 0.9754        | 0.87  | 1500 | 0.9729          |
| 0.9785        | 0.9   | 1550 | 0.9727          |
| 0.9828        | 0.93  | 1600 | 0.9725          |
| 0.9951        | 0.95  | 1650 | 0.9724          |
| 0.983         | 0.98  | 1700 | 0.9724          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2