---
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-v4
  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-v4

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: 0.4623

## 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    | 0.7933          |
| 0.8309        | 0.17  | 10   | 0.7250          |
| 0.6972        | 0.26  | 15   | 0.6792          |
| 0.6841        | 0.34  | 20   | 0.6448          |
| 0.645         | 0.43  | 25   | 0.6158          |
| 0.626         | 0.52  | 30   | 0.5929          |
| 0.5645        | 0.6   | 35   | 0.5719          |
| 0.5722        | 0.69  | 40   | 0.5545          |
| 0.5489        | 0.78  | 45   | 0.5385          |
| 0.5206        | 0.86  | 50   | 0.5283          |
| 0.4599        | 0.95  | 55   | 0.5171          |
| 0.5232        | 1.03  | 60   | 0.5082          |
| 0.4798        | 1.12  | 65   | 0.5032          |
| 0.3585        | 1.21  | 70   | 0.4984          |
| 0.3923        | 1.29  | 75   | 0.4899          |
| 0.3915        | 1.38  | 80   | 0.4825          |
| 0.3845        | 1.47  | 85   | 0.4758          |
| 0.3768        | 1.55  | 90   | 0.4752          |
| 0.3928        | 1.64  | 95   | 0.4668          |
| 0.3986        | 1.72  | 100  | 0.4632          |
| 0.3495        | 1.81  | 105  | 0.4607          |
| 0.4014        | 1.9   | 110  | 0.4563          |
| 0.3902        | 1.98  | 115  | 0.4519          |
| 0.3081        | 2.07  | 120  | 0.4656          |
| 0.3204        | 2.16  | 125  | 0.4569          |
| 0.2844        | 2.24  | 130  | 0.4605          |
| 0.2501        | 2.33  | 135  | 0.4595          |
| 0.2723        | 2.41  | 140  | 0.4547          |
| 0.2979        | 2.5   | 145  | 0.4662          |
| 0.2884        | 2.59  | 150  | 0.4548          |
| 0.2944        | 2.67  | 155  | 0.4587          |
| 0.2575        | 2.76  | 160  | 0.4542          |
| 0.2558        | 2.84  | 165  | 0.4499          |
| 0.2165        | 2.93  | 170  | 0.4511          |
| 0.2806        | 3.02  | 175  | 0.4484          |
| 0.1799        | 3.1   | 180  | 0.4799          |
| 0.1877        | 3.19  | 185  | 0.4608          |
| 0.1918        | 3.28  | 190  | 0.4738          |
| 0.1812        | 3.36  | 195  | 0.4665          |
| 0.199         | 3.45  | 200  | 0.4714          |
| 0.1581        | 3.53  | 205  | 0.4699          |
| 0.1918        | 3.62  | 210  | 0.4613          |
| 0.2052        | 3.71  | 215  | 0.4667          |
| 0.1893        | 3.79  | 220  | 0.4626          |
| 0.2177        | 3.88  | 225  | 0.4606          |
| 0.2196        | 3.97  | 230  | 0.4623          |


### Framework versions

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