---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- generated_from_trainer
model-index:
- name: radia-fine-tune-mistral-7b-lora
  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. -->

# radia-fine-tune-mistral-7b-lora

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4616

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.038         | 0.09  | 5    | 0.7930          |
| 0.8312        | 0.17  | 10   | 0.7245          |
| 0.6972        | 0.26  | 15   | 0.6791          |
| 0.6848        | 0.34  | 20   | 0.6456          |
| 0.6457        | 0.43  | 25   | 0.6159          |
| 0.6261        | 0.52  | 30   | 0.5927          |
| 0.5639        | 0.6   | 35   | 0.5718          |
| 0.5723        | 0.69  | 40   | 0.5540          |
| 0.5473        | 0.78  | 45   | 0.5389          |
| 0.5209        | 0.86  | 50   | 0.5284          |
| 0.4591        | 0.95  | 55   | 0.5177          |
| 0.5233        | 1.03  | 60   | 0.5080          |
| 0.4805        | 1.12  | 65   | 0.5030          |
| 0.3604        | 1.21  | 70   | 0.4987          |
| 0.3927        | 1.29  | 75   | 0.4907          |
| 0.3934        | 1.38  | 80   | 0.4849          |
| 0.3859        | 1.47  | 85   | 0.4761          |
| 0.3779        | 1.55  | 90   | 0.4748          |
| 0.3929        | 1.64  | 95   | 0.4655          |
| 0.3973        | 1.72  | 100  | 0.4635          |
| 0.3512        | 1.81  | 105  | 0.4599          |
| 0.4027        | 1.9   | 110  | 0.4575          |
| 0.3917        | 1.98  | 115  | 0.4504          |
| 0.3069        | 2.07  | 120  | 0.4667          |
| 0.3203        | 2.16  | 125  | 0.4569          |
| 0.2807        | 2.24  | 130  | 0.4615          |
| 0.2471        | 2.33  | 135  | 0.4612          |
| 0.2724        | 2.41  | 140  | 0.4553          |
| 0.2976        | 2.5   | 145  | 0.4665          |
| 0.2873        | 2.59  | 150  | 0.4551          |
| 0.2968        | 2.67  | 155  | 0.4568          |
| 0.2577        | 2.76  | 160  | 0.4564          |
| 0.2569        | 2.84  | 165  | 0.4496          |
| 0.2167        | 2.93  | 170  | 0.4486          |
| 0.2785        | 3.02  | 175  | 0.4518          |
| 0.176         | 3.1   | 180  | 0.4798          |
| 0.1909        | 3.19  | 185  | 0.4588          |
| 0.1883        | 3.28  | 190  | 0.4768          |
| 0.1806        | 3.36  | 195  | 0.4693          |
| 0.1998        | 3.45  | 200  | 0.4732          |
| 0.1573        | 3.53  | 205  | 0.4745          |
| 0.1908        | 3.62  | 210  | 0.4627          |
| 0.2042        | 3.71  | 215  | 0.4695          |
| 0.1918        | 3.79  | 220  | 0.4620          |
| 0.2163        | 3.88  | 225  | 0.4574          |
| 0.2189        | 3.97  | 230  | 0.4616          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0