---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
model-index:
- name: finetune_cs_20_cot
  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_cs_20_cot

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: 2.9873

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7119        | 1.0   | 150  | 1.6237          |
| 1.5767        | 2.0   | 300  | 1.6768          |
| 0.5982        | 3.0   | 450  | 1.9207          |
| 0.5098        | 4.0   | 600  | 2.1488          |
| 0.3085        | 5.0   | 750  | 2.2398          |
| 0.2595        | 6.0   | 900  | 2.2685          |
| 0.2118        | 7.0   | 1050 | 2.4754          |
| 0.2221        | 8.0   | 1200 | 2.4747          |
| 0.1796        | 9.0   | 1350 | 2.5642          |
| 0.1706        | 10.0  | 1500 | 2.5938          |
| 0.161         | 11.0  | 1650 | 2.6814          |
| 0.1484        | 12.0  | 1800 | 2.7009          |
| 0.1408        | 13.0  | 1950 | 2.7635          |
| 0.1472        | 14.0  | 2100 | 2.7593          |
| 0.154         | 15.0  | 2250 | 2.8357          |
| 0.1455        | 16.0  | 2400 | 2.8705          |
| 0.164         | 17.0  | 2550 | 2.9052          |
| 0.1613        | 18.0  | 2700 | 2.9437          |
| 0.1397        | 19.0  | 2850 | 2.9716          |
| 0.1177        | 20.0  | 3000 | 2.9873          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0