|
|
--- |
|
|
license: mit |
|
|
base_model: vinai/phobert-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: DACN3_LVC |
|
|
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. --> |
|
|
|
|
|
# DACN3_LVC |
|
|
|
|
|
This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 3.6795 |
|
|
|
|
|
## 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: 16 |
|
|
- eval_batch_size: 16 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 50 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
|
| No log | 1.0 | 347 | 1.6767 | |
|
|
| 0.233 | 2.0 | 694 | 1.7635 | |
|
|
| 0.189 | 3.0 | 1041 | 1.9054 | |
|
|
| 0.189 | 4.0 | 1388 | 2.2254 | |
|
|
| 0.1566 | 5.0 | 1735 | 2.1978 | |
|
|
| 0.1968 | 6.0 | 2082 | 2.1144 | |
|
|
| 0.1968 | 7.0 | 2429 | 2.2885 | |
|
|
| 0.1541 | 8.0 | 2776 | 2.3121 | |
|
|
| 0.1055 | 9.0 | 3123 | 2.5475 | |
|
|
| 0.1055 | 10.0 | 3470 | 2.7483 | |
|
|
| 0.09 | 11.0 | 3817 | 2.7914 | |
|
|
| 0.0716 | 12.0 | 4164 | 2.9014 | |
|
|
| 0.0469 | 13.0 | 4511 | 3.1734 | |
|
|
| 0.0469 | 14.0 | 4858 | 3.0398 | |
|
|
| 0.0571 | 15.0 | 5205 | 3.3835 | |
|
|
| 0.0646 | 16.0 | 5552 | 3.0768 | |
|
|
| 0.0646 | 17.0 | 5899 | 3.2561 | |
|
|
| 0.0263 | 18.0 | 6246 | 3.3902 | |
|
|
| 0.0395 | 19.0 | 6593 | 3.3001 | |
|
|
| 0.0395 | 20.0 | 6940 | 3.3090 | |
|
|
| 0.0258 | 21.0 | 7287 | 3.3304 | |
|
|
| 0.0284 | 22.0 | 7634 | 3.6674 | |
|
|
| 0.0284 | 23.0 | 7981 | 3.4840 | |
|
|
| 0.0227 | 24.0 | 8328 | 3.5787 | |
|
|
| 0.0262 | 25.0 | 8675 | 3.4169 | |
|
|
| 0.0263 | 26.0 | 9022 | 3.4694 | |
|
|
| 0.0263 | 27.0 | 9369 | 3.5745 | |
|
|
| 0.027 | 28.0 | 9716 | 3.5336 | |
|
|
| 0.0175 | 29.0 | 10063 | 3.5374 | |
|
|
| 0.0175 | 30.0 | 10410 | 3.5704 | |
|
|
| 0.0185 | 31.0 | 10757 | 3.5223 | |
|
|
| 0.012 | 32.0 | 11104 | 3.4871 | |
|
|
| 0.012 | 33.0 | 11451 | 3.6621 | |
|
|
| 0.0117 | 34.0 | 11798 | 3.4769 | |
|
|
| 0.0106 | 35.0 | 12145 | 3.6008 | |
|
|
| 0.0106 | 36.0 | 12492 | 3.8597 | |
|
|
| 0.0104 | 37.0 | 12839 | 3.5269 | |
|
|
| 0.0076 | 38.0 | 13186 | 3.6466 | |
|
|
| 0.0051 | 39.0 | 13533 | 3.6385 | |
|
|
| 0.0051 | 40.0 | 13880 | 3.6788 | |
|
|
| 0.0069 | 41.0 | 14227 | 3.6508 | |
|
|
| 0.0033 | 42.0 | 14574 | 3.6343 | |
|
|
| 0.0033 | 43.0 | 14921 | 3.5916 | |
|
|
| 0.0033 | 44.0 | 15268 | 3.5940 | |
|
|
| 0.0033 | 45.0 | 15615 | 3.5818 | |
|
|
| 0.0033 | 46.0 | 15962 | 3.6118 | |
|
|
| 0.0024 | 47.0 | 16309 | 3.5790 | |
|
|
| 0.0012 | 48.0 | 16656 | 3.5841 | |
|
|
| 0.0028 | 49.0 | 17003 | 3.6151 | |
|
|
| 0.0028 | 50.0 | 17350 | 3.6149 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.2 |
|
|
- Pytorch 2.5.1+cu121 |
|
|
- Datasets 2.16.1 |
|
|
- Tokenizers 0.15.2 |
|
|
|
