---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama7b-protgen
  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. -->

# llama7b-protgen

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: 6.7466

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.4347        | 0.05  | 100  | 8.3863          |
| 8.3045        | 0.1   | 200  | 8.2328          |
| 7.9602        | 0.15  | 300  | 7.9333          |
| 7.4512        | 0.2   | 400  | 7.6350          |
| 5.938         | 0.25  | 500  | 7.3528          |
| 4.9679        | 0.3   | 600  | 6.9324          |
| 3.9455        | 0.35  | 700  | 6.6334          |
| 2.8044        | 0.4   | 800  | 6.6159          |
| 2.071         | 0.45  | 900  | 6.5350          |
| 1.5644        | 0.5   | 1000 | 6.3780          |
| 1.2187        | 0.55  | 1100 | 6.3079          |
| 0.8425        | 0.6   | 1200 | 6.4287          |
| 0.6849        | 0.65  | 1300 | 6.3898          |
| 0.5457        | 0.7   | 1400 | 6.5978          |
| 0.4533        | 0.75  | 1500 | 6.4167          |
| 0.2974        | 0.8   | 1600 | 6.4443          |
| 0.2676        | 0.85  | 1700 | 6.3087          |
| 0.2395        | 0.9   | 1800 | 6.5467          |
| 0.2042        | 0.95  | 1900 | 6.4028          |
| 0.2042        | 1.0   | 2000 | 6.7466          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0