---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
model-index:
- name: finetune_mc_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_mc_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: 4.0612

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8917        | 1.0   | 70   | 1.7411          |
| 0.2135        | 2.0   | 140  | 2.3727          |
| 0.1702        | 3.0   | 210  | 2.5470          |
| 0.1234        | 4.0   | 280  | 2.8131          |
| 0.0843        | 5.0   | 350  | 3.0446          |
| 0.0478        | 6.0   | 420  | 3.1141          |
| 0.0473        | 7.0   | 490  | 3.2304          |
| 0.0544        | 8.0   | 560  | 3.3806          |
| 0.0289        | 9.0   | 630  | 3.4231          |
| 0.0202        | 10.0  | 700  | 3.5503          |
| 0.0214        | 11.0  | 770  | 3.5892          |
| 0.0261        | 12.0  | 840  | 3.7211          |
| 0.0232        | 13.0  | 910  | 3.8148          |
| 0.0242        | 14.0  | 980  | 3.8177          |
| 0.0198        | 15.0  | 1050 | 3.9079          |
| 0.018         | 16.0  | 1120 | 3.9320          |
| 0.0196        | 17.0  | 1190 | 3.9807          |
| 0.0179        | 18.0  | 1260 | 4.0263          |
| 0.0194        | 19.0  | 1330 | 4.0520          |
| 0.0169        | 20.0  | 1400 | 4.0612          |


### Framework versions

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