---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Summary_M2_1000steps_1e7rate_SFT2
  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. -->

# Summary_M2_1000steps_1e7rate_SFT2

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: 0.5731

## 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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8232        | 0.2   | 50   | 1.7949          |
| 1.53          | 0.4   | 100  | 1.4490          |
| 1.0256        | 0.6   | 150  | 0.9395          |
| 0.6284        | 0.8   | 200  | 0.6030          |
| 0.5923        | 1.0   | 250  | 0.5887          |
| 0.5851        | 1.2   | 300  | 0.5835          |
| 0.675         | 1.4   | 350  | 0.5802          |
| 0.5931        | 1.6   | 400  | 0.5780          |
| 0.5629        | 1.8   | 450  | 0.5765          |
| 0.6207        | 2.0   | 500  | 0.5753          |
| 0.5956        | 2.2   | 550  | 0.5745          |
| 0.5902        | 2.4   | 600  | 0.5740          |
| 0.6132        | 2.6   | 650  | 0.5736          |
| 0.5964        | 2.8   | 700  | 0.5733          |
| 0.5844        | 3.0   | 750  | 0.5732          |
| 0.6054        | 3.2   | 800  | 0.5731          |
| 0.6079        | 3.4   | 850  | 0.5731          |
| 0.6549        | 3.6   | 900  | 0.5731          |
| 0.5838        | 3.8   | 950  | 0.5731          |
| 0.5724        | 4.0   | 1000 | 0.5731          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1