quan-1.8b-chat / README.md
qnguyen3's picture
Update README.md
3b648e8 verified
|
raw
history blame
2.16 kB
---
license: other
base_model: KnutJaegersberg/Qwen-1_8B-Llamafied
tags:
- generated_from_trainer
model-index:
- name: qwen-1.8b-vi
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)
# Quan-1.8b
Qwen-1.8B finetuned on bilingual English-Vietnamese Data.
## Prompt Template
ChatML, same as VinaLlama
```
<|im_start|>system
Bạn là một trợ lí AI hữu ích. Hãy trả lời người dùng một cách chính xác.
<|im_end|>
<|im_start|>user
Hello world!<|im_end|>
<|im_start|>assistant
```
This model is a fine-tuned version of [KnutJaegersberg/Qwen-1_8B-Llamafied](https://huggingface.co/KnutJaegersberg/Qwen-1_8B-Llamafied) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8096
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8123 | 1.02 | 2356 | 0.8183 |
| 0.7358 | 2.02 | 4713 | 0.7790 |
| 0.6379 | 3.02 | 7071 | 0.7822 |
| 0.5762 | 3.94 | 9252 | 0.8096 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1