|
--- |
|
license: other |
|
base_model: meta-llama/Llama-2-7b-hf |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: hyporadise |
|
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. --> |
|
|
|
# LLaMa-2-Hyporadise-pre-trained |
|
|
|
Contributors: Yen-Ting Lin, Huck Yang |
|
|
|
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 hyporadise dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3419 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 256 |
|
- total_eval_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 20 |
|
- num_epochs: 3.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.3436 | 0.21 | 100 | 0.3495 | |
|
| 0.3306 | 0.42 | 200 | 0.3352 | |
|
| 0.3417 | 0.63 | 300 | 0.3245 | |
|
| 0.3154 | 0.84 | 400 | 0.3160 | |
|
| 0.1577 | 1.05 | 500 | 0.3239 | |
|
| 0.159 | 1.26 | 600 | 0.3230 | |
|
| 0.1493 | 1.48 | 700 | 0.3176 | |
|
| 0.1498 | 1.69 | 800 | 0.3158 | |
|
| 0.147 | 1.9 | 900 | 0.3104 | |
|
| 0.0583 | 2.11 | 1000 | 0.3452 | |
|
| 0.0547 | 2.32 | 1100 | 0.3395 | |
|
| 0.0589 | 2.53 | 1200 | 0.3417 | |
|
| 0.0593 | 2.74 | 1300 | 0.3414 | |
|
| 0.0624 | 2.95 | 1400 | 0.3420 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
