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---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: IE_M2_650steps_1e8rate_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. -->

# IE_M2_650steps_1e8rate_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: 1.9102

## 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-08
- 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: 650

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8842        | 0.4   | 50   | 1.9129          |
| 1.9556        | 0.8   | 100  | 1.9129          |
| 2.0185        | 1.2   | 150  | 1.9121          |
| 1.9349        | 1.6   | 200  | 1.9112          |
| 1.975         | 2.0   | 250  | 1.9107          |
| 2.0088        | 2.4   | 300  | 1.9104          |
| 2.0245        | 2.8   | 350  | 1.9106          |
| 1.911         | 3.2   | 400  | 1.9101          |
| 2.0222        | 3.6   | 450  | 1.9105          |
| 1.9025        | 4.0   | 500  | 1.9104          |
| 2.0573        | 4.4   | 550  | 1.9102          |
| 1.9739        | 4.8   | 600  | 1.9102          |
| 2.001         | 5.2   | 650  | 1.9102          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1