---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Summary4500_M2_1000steps_1e7rate_SFT
  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. -->

# Summary4500_M2_1000steps_1e7rate_SFT

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: 0.0586

## 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-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.0168        | 0.0112 | 50   | 1.9854          |
| 1.3848        | 0.0224 | 100  | 1.3059          |
| 0.1374        | 0.0336 | 150  | 0.1142          |
| 0.0099        | 0.0448 | 200  | 0.0587          |
| 0.0076        | 0.0559 | 250  | 0.0581          |
| 0.0073        | 0.0671 | 300  | 0.0580          |
| 0.0071        | 0.0783 | 350  | 0.0587          |
| 0.0071        | 0.0895 | 400  | 0.0586          |
| 0.0069        | 0.1007 | 450  | 0.0589          |
| 0.0068        | 0.1119 | 500  | 0.0586          |
| 0.0068        | 0.1231 | 550  | 0.0586          |
| 0.0067        | 0.1343 | 600  | 0.0588          |
| 0.0067        | 0.1454 | 650  | 0.0589          |
| 0.0066        | 0.1566 | 700  | 0.0590          |
| 0.0066        | 0.1678 | 750  | 0.0587          |
| 0.0066        | 0.1790 | 800  | 0.0588          |
| 0.0066        | 0.1902 | 850  | 0.0588          |
| 0.0066        | 0.2014 | 900  | 0.0586          |
| 0.0066        | 0.2126 | 950  | 0.0586          |
| 0.0066        | 0.2238 | 1000 | 0.0586          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1