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---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: ckpts/llama2-7b-viettel_v3.2_2epoch
  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. -->

[<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)
# ckpts/llama2-7b-viettel_v3.2_2epoch

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3727

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4378        | 0.12  | 200  | 0.4331          |
| 0.4266        | 0.24  | 400  | 0.4187          |
| 0.4199        | 0.37  | 600  | 0.4086          |
| 0.4024        | 0.49  | 800  | 0.4016          |
| 0.4003        | 0.61  | 1000 | 0.3966          |
| 0.3849        | 0.73  | 1200 | 0.3914          |
| 0.3814        | 0.86  | 1400 | 0.3865          |
| 0.3825        | 0.98  | 1600 | 0.3831          |
| 0.3557        | 1.1   | 1800 | 0.3812          |
| 0.3531        | 1.22  | 2000 | 0.3789          |
| 0.3444        | 1.35  | 2200 | 0.3771          |
| 0.3411        | 1.47  | 2400 | 0.3752          |
| 0.35          | 1.59  | 2600 | 0.3738          |
| 0.3586        | 1.71  | 2800 | 0.3733          |
| 0.349         | 1.84  | 3000 | 0.3728          |
| 0.357         | 1.96  | 3200 | 0.3727          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.14.0