---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Summary4500_M2_750steps_1e5rate_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_750steps_1e5rate_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: 0.4197

## 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-05
- 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: 750

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4687        | 0.0447 | 50   | 0.5176          |
| 0.5069        | 0.0895 | 100  | 0.5367          |
| 0.5289        | 0.1342 | 150  | 0.5178          |
| 0.4896        | 0.1790 | 200  | 0.5124          |
| 0.4982        | 0.2237 | 250  | 0.5096          |
| 0.4595        | 0.2685 | 300  | 0.5040          |
| 0.4998        | 0.3132 | 350  | 0.4854          |
| 0.4571        | 0.3579 | 400  | 0.4713          |
| 0.4477        | 0.4027 | 450  | 0.4577          |
| 0.4286        | 0.4474 | 500  | 0.4466          |
| 0.4113        | 0.4922 | 550  | 0.4338          |
| 0.4044        | 0.5369 | 600  | 0.4262          |
| 0.3802        | 0.5817 | 650  | 0.4213          |
| 0.4059        | 0.6264 | 700  | 0.4199          |
| 0.4289        | 0.6711 | 750  | 0.4197          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.0.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1