---
base_model: mistralai/Mistral-7B-v0.1
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4476

## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 17
- training_steps: 1792

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.8156        | 0.1115 | 50   | 1.7682          |
| 1.6754        | 0.2230 | 100  | 1.6347          |
| 1.5257        | 0.3344 | 150  | 1.5543          |
| 1.5435        | 0.4459 | 200  | 1.5301          |
| 1.613         | 0.5574 | 250  | 1.5579          |
| 1.6178        | 0.6689 | 300  | 1.6006          |
| 1.675         | 0.7804 | 350  | 1.5209          |
| 1.5046        | 0.8919 | 400  | 1.5203          |
| 1.5977        | 1.0033 | 450  | 1.5253          |
| 1.5303        | 1.1148 | 500  | 1.4984          |
| 1.4748        | 1.2263 | 550  | 1.5073          |
| 1.4955        | 1.3378 | 600  | 1.4998          |
| 1.5737        | 1.4493 | 650  | 1.5405          |
| 1.5662        | 1.5608 | 700  | 1.5147          |
| 1.417         | 1.6722 | 750  | 1.5047          |
| 1.5732        | 1.7837 | 800  | 1.4768          |
| 1.5077        | 1.8952 | 850  | 1.4948          |
| 1.5634        | 2.0067 | 900  | 1.4768          |
| 1.5219        | 2.1182 | 950  | 1.4752          |
| 1.4073        | 2.2297 | 1000 | 1.4776          |
| 1.4915        | 2.3411 | 1050 | 1.4799          |
| 1.4585        | 2.4526 | 1100 | 1.4868          |
| 1.4979        | 2.5641 | 1150 | 1.4703          |
| 1.4755        | 2.6756 | 1200 | 1.4617          |
| 1.4167        | 2.7871 | 1250 | 1.4576          |
| 1.5095        | 2.8986 | 1300 | 1.4651          |
| 1.477         | 3.0100 | 1350 | 1.4526          |
| 1.4495        | 3.1215 | 1400 | 1.4660          |
| 1.5609        | 3.2330 | 1450 | 1.4547          |
| 1.4319        | 3.3445 | 1500 | 1.4478          |
| 1.3469        | 3.4560 | 1550 | 1.4597          |
| 1.4454        | 3.5674 | 1600 | 1.4478          |
| 1.4071        | 3.6789 | 1650 | 1.4506          |
| 1.3686        | 3.7904 | 1700 | 1.4485          |
| 1.4958        | 3.9019 | 1750 | 1.4476          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1