---
license: llama2
base_model: lmsys/vicuna-7b-v1.5
tags:
- generated_from_trainer
model-index:
- name: mc_cot_16
  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. -->

# mc_cot_16

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: 3.0303

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1538        | 1.0   | 4    | 2.1552          |
| 1.7905        | 2.0   | 8    | 1.9012          |
| 1.4229        | 3.0   | 12   | 1.7686          |
| 1.3834        | 4.0   | 16   | 1.7070          |
| 1.4421        | 5.0   | 20   | 1.7308          |
| 0.9003        | 6.0   | 24   | 1.7646          |
| 0.7013        | 7.0   | 28   | 1.9070          |
| 0.6291        | 8.0   | 32   | 2.0078          |
| 0.3314        | 9.0   | 36   | 2.2682          |
| 0.1554        | 10.0  | 40   | 2.3624          |
| 0.0814        | 11.0  | 44   | 2.6523          |
| 0.0499        | 12.0  | 48   | 2.7565          |
| 0.0216        | 13.0  | 52   | 2.8505          |
| 0.0197        | 14.0  | 56   | 2.9170          |
| 0.0174        | 15.0  | 60   | 2.9433          |
| 0.0174        | 16.0  | 64   | 2.9683          |
| 0.0145        | 17.0  | 68   | 2.9966          |
| 0.013         | 18.0  | 72   | 3.0193          |
| 0.0151        | 19.0  | 76   | 3.0277          |
| 0.0145        | 20.0  | 80   | 3.0303          |


### Framework versions

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