---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
model-index:
- name: finetune_race_20
  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. -->

# finetune_race_20

This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4669

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2823        | 1.0   | 150  | 1.4463          |
| 0.7207        | 2.0   | 300  | 1.5249          |
| 0.4983        | 3.0   | 450  | 1.6580          |
| 0.5956        | 4.0   | 600  | 1.8347          |
| 0.1806        | 5.0   | 750  | 2.0078          |
| 0.1439        | 6.0   | 900  | 2.2482          |
| 0.1399        | 7.0   | 1050 | 2.3858          |
| 0.0826        | 8.0   | 1200 | 2.4455          |
| 0.0878        | 9.0   | 1350 | 2.5889          |
| 0.0564        | 10.0  | 1500 | 2.7918          |
| 0.0641        | 11.0  | 1650 | 2.7968          |
| 0.0522        | 12.0  | 1800 | 2.7144          |
| 0.0491        | 13.0  | 1950 | 2.9539          |
| 0.0436        | 14.0  | 2100 | 2.9602          |
| 0.0431        | 15.0  | 2250 | 3.1613          |
| 0.0449        | 16.0  | 2400 | 3.2197          |
| 0.0516        | 17.0  | 2550 | 3.3331          |
| 0.0432        | 18.0  | 2700 | 3.4157          |
| 0.0448        | 19.0  | 2850 | 3.4384          |
| 0.0416        | 20.0  | 3000 | 3.4669          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1