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---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: ckpts/llama2-13b-viettel_v3.2_1epoch
  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/llama2-13b-viettel_v3.2_1epoch

This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the our custom dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3534
### 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: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4028        | 0.08  | 200  | 0.3990          |
| 0.3973        | 0.16  | 400  | 0.3866          |
| 0.3832        | 0.24  | 600  | 0.3790          |
| 0.3844        | 0.33  | 800  | 0.3728          |
| 0.3703        | 0.41  | 1000 | 0.3676          |
| 0.3682        | 0.49  | 1200 | 0.3640          |
| 0.3669        | 0.57  | 1400 | 0.3606          |
| 0.3677        | 0.65  | 1600 | 0.3580          |
| 0.3545        | 0.73  | 1800 | 0.3556          |
| 0.3593        | 0.82  | 2000 | 0.3543          |
| 0.3442        | 0.9   | 2200 | 0.3536          |
| 0.363         | 0.98  | 2400 | 0.3534          |


### Framework versions

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