---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_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. -->

# llama_finetune_cs_20_cot

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3122

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5397        | 1.0   | 150  | 1.4682          |
| 1.2842        | 2.0   | 300  | 1.5033          |
| 1.0418        | 3.0   | 450  | 1.7145          |
| 0.3202        | 4.0   | 600  | 1.9554          |
| 0.3109        | 5.0   | 750  | 2.2233          |
| 0.3597        | 6.0   | 900  | 2.4190          |
| 0.1135        | 7.0   | 1050 | 2.4910          |
| 0.0863        | 8.0   | 1200 | 2.5746          |
| 0.1082        | 9.0   | 1350 | 2.6889          |
| 0.0757        | 10.0  | 1500 | 2.7235          |
| 0.0818        | 11.0  | 1650 | 2.8289          |
| 0.0698        | 12.0  | 1800 | 2.8434          |
| 0.0714        | 13.0  | 1950 | 2.7956          |
| 0.0779        | 14.0  | 2100 | 2.9733          |
| 0.067         | 15.0  | 2250 | 3.0476          |
| 0.065         | 16.0  | 2400 | 3.1342          |
| 0.067         | 17.0  | 2550 | 3.1901          |
| 0.0777        | 18.0  | 2700 | 3.2490          |
| 0.0647        | 19.0  | 2850 | 3.3113          |
| 0.0661        | 20.0  | 3000 | 3.3122          |


### Framework versions

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