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

# UTI_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: 1.1047

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.4021        | 0.3333  | 25   | 2.3941          |
| 2.3235        | 0.6667  | 50   | 2.2471          |
| 2.0863        | 1.0     | 75   | 1.9386          |
| 1.6662        | 1.3333  | 100  | 1.5791          |
| 1.2956        | 1.6667  | 125  | 1.2544          |
| 1.214         | 2.0     | 150  | 1.2116          |
| 1.202         | 2.3333  | 175  | 1.1861          |
| 1.1813        | 2.6667  | 200  | 1.1668          |
| 1.1696        | 3.0     | 225  | 1.1528          |
| 1.1052        | 3.3333  | 250  | 1.1412          |
| 1.0614        | 3.6667  | 275  | 1.1329          |
| 1.1106        | 4.0     | 300  | 1.1271          |
| 1.1019        | 4.3333  | 325  | 1.1228          |
| 1.0691        | 4.6667  | 350  | 1.1212          |
| 1.0947        | 5.0     | 375  | 1.1153          |
| 1.0689        | 5.3333  | 400  | 1.1134          |
| 1.0598        | 5.6667  | 425  | 1.1116          |
| 1.0459        | 6.0     | 450  | 1.1111          |
| 1.0518        | 6.3333  | 475  | 1.1097          |
| 1.045         | 6.6667  | 500  | 1.1092          |
| 1.0658        | 7.0     | 525  | 1.1066          |
| 1.0706        | 7.3333  | 550  | 1.1067          |
| 1.0514        | 7.6667  | 575  | 1.1057          |
| 1.0412        | 8.0     | 600  | 1.1063          |
| 1.0455        | 8.3333  | 625  | 1.1052          |
| 0.9657        | 8.6667  | 650  | 1.1057          |
| 1.1015        | 9.0     | 675  | 1.1052          |
| 1.0294        | 9.3333  | 700  | 1.1051          |
| 1.0399        | 9.6667  | 725  | 1.1052          |
| 1.1125        | 10.0    | 750  | 1.1047          |
| 1.0219        | 10.3333 | 775  | 1.1046          |
| 0.9862        | 10.6667 | 800  | 1.1048          |
| 1.0682        | 11.0    | 825  | 1.1049          |
| 1.0587        | 11.3333 | 850  | 1.1049          |
| 1.0217        | 11.6667 | 875  | 1.1051          |
| 1.0547        | 12.0    | 900  | 1.1047          |
| 1.0047        | 12.3333 | 925  | 1.1047          |
| 1.021         | 12.6667 | 950  | 1.1047          |
| 1.0528        | 13.0    | 975  | 1.1047          |
| 1.0385        | 13.3333 | 1000 | 1.1047          |


### Framework versions

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