|
--- |
|
base_model: vinai/phobert-base-v2 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: CS505-Classifier-T4_predictLabel_a1_v4 |
|
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. --> |
|
|
|
# CS505-Classifier-T4_predictLabel_a1_v4 |
|
|
|
This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co./vinai/phobert-base-v2) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0046 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 40 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 0.98 | 48 | 1.0265 | |
|
| No log | 1.96 | 96 | 0.5809 | |
|
| No log | 2.94 | 144 | 0.3461 | |
|
| No log | 3.92 | 192 | 0.2725 | |
|
| No log | 4.9 | 240 | 0.2168 | |
|
| No log | 5.88 | 288 | 0.1728 | |
|
| No log | 6.86 | 336 | 0.1516 | |
|
| No log | 7.84 | 384 | 0.1076 | |
|
| No log | 8.82 | 432 | 0.0783 | |
|
| No log | 9.8 | 480 | 0.0653 | |
|
| 0.4162 | 10.78 | 528 | 0.0473 | |
|
| 0.4162 | 11.76 | 576 | 0.0413 | |
|
| 0.4162 | 12.73 | 624 | 0.0344 | |
|
| 0.4162 | 13.71 | 672 | 0.0253 | |
|
| 0.4162 | 14.69 | 720 | 0.0244 | |
|
| 0.4162 | 15.67 | 768 | 0.0204 | |
|
| 0.4162 | 16.65 | 816 | 0.0210 | |
|
| 0.4162 | 17.63 | 864 | 0.0168 | |
|
| 0.4162 | 18.61 | 912 | 0.0155 | |
|
| 0.4162 | 19.59 | 960 | 0.0132 | |
|
| 0.0375 | 20.57 | 1008 | 0.0130 | |
|
| 0.0375 | 21.55 | 1056 | 0.0097 | |
|
| 0.0375 | 22.53 | 1104 | 0.0088 | |
|
| 0.0375 | 23.51 | 1152 | 0.0081 | |
|
| 0.0375 | 24.49 | 1200 | 0.0080 | |
|
| 0.0375 | 25.47 | 1248 | 0.0069 | |
|
| 0.0375 | 26.45 | 1296 | 0.0065 | |
|
| 0.0375 | 27.43 | 1344 | 0.0062 | |
|
| 0.0375 | 28.41 | 1392 | 0.0060 | |
|
| 0.0375 | 29.39 | 1440 | 0.0056 | |
|
| 0.0375 | 30.37 | 1488 | 0.0055 | |
|
| 0.0114 | 31.35 | 1536 | 0.0053 | |
|
| 0.0114 | 32.33 | 1584 | 0.0052 | |
|
| 0.0114 | 33.31 | 1632 | 0.0051 | |
|
| 0.0114 | 34.29 | 1680 | 0.0049 | |
|
| 0.0114 | 35.27 | 1728 | 0.0048 | |
|
| 0.0114 | 36.24 | 1776 | 0.0048 | |
|
| 0.0114 | 37.22 | 1824 | 0.0047 | |
|
| 0.0114 | 38.2 | 1872 | 0.0047 | |
|
| 0.0114 | 39.18 | 1920 | 0.0046 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
