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

# llama_finetune_cs_20

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: 3.0872

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6881        | 1.0   | 150  | 1.6028          |
| 1.3532        | 2.0   | 300  | 1.6693          |
| 0.9084        | 3.0   | 450  | 1.8783          |
| 0.4352        | 4.0   | 600  | 2.0825          |
| 0.374         | 5.0   | 750  | 2.1988          |
| 0.2596        | 6.0   | 900  | 2.2869          |
| 0.2316        | 7.0   | 1050 | 2.3945          |
| 0.1754        | 8.0   | 1200 | 2.5528          |
| 0.1698        | 9.0   | 1350 | 2.6226          |
| 0.1371        | 10.0  | 1500 | 2.5997          |
| 0.1702        | 11.0  | 1650 | 2.7153          |
| 0.1391        | 12.0  | 1800 | 2.6888          |
| 0.1894        | 13.0  | 1950 | 2.7324          |
| 0.1504        | 14.0  | 2100 | 2.8534          |
| 0.132         | 15.0  | 2250 | 2.8804          |
| 0.1585        | 16.0  | 2400 | 2.9148          |
| 0.1497        | 17.0  | 2550 | 2.9550          |
| 0.1099        | 18.0  | 2700 | 3.0002          |
| 0.1321        | 19.0  | 2850 | 3.0532          |
| 0.11          | 20.0  | 3000 | 3.0872          |


### Framework versions

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