---
base_model: NousResearch/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: out
  results: []
---

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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# out

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9443

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 3
- total_eval_batch_size: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0254        | 0.03  | 1    | 3.0959          |
| 3.2648        | 0.06  | 2    | 3.0959          |
| 3.0345        | 0.12  | 4    | 1.6018          |
| 1.4912        | 0.18  | 6    | 1.4104          |
| 1.4298        | 0.24  | 8    | 1.2483          |
| 1.2217        | 0.29  | 10   | 1.1785          |
| 1.1975        | 0.35  | 12   | 1.1200          |
| 1.1377        | 0.41  | 14   | 1.0922          |
| 1.0991        | 0.47  | 16   | 1.0625          |
| 0.9783        | 0.53  | 18   | 1.0422          |
| 1.0558        | 0.59  | 20   | 1.0100          |
| 0.9894        | 0.65  | 22   | 0.9902          |
| 0.9677        | 0.71  | 24   | 0.9780          |
| 0.9782        | 0.76  | 26   | 0.9679          |
| 0.9944        | 0.82  | 28   | 0.9595          |
| 0.9245        | 0.88  | 30   | 0.9509          |
| 0.9676        | 0.94  | 32   | 0.9468          |
| 1.0653        | 1.0   | 34   | 0.9443          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1