|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: vinai/phobert-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
model-index: |
|
|
- name: phobert-human-tl-seg-seed-6969 |
|
|
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. --> |
|
|
|
|
|
# phobert-human-tl-seg-seed-6969 |
|
|
|
|
|
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: 0.4483 |
|
|
- Accuracy: 0.8432 |
|
|
- Precision: 0.6507 |
|
|
- Recall: 0.4682 |
|
|
- F1: 0.4928 |
|
|
|
|
|
## 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: 0.0001 |
|
|
- train_batch_size: 64 |
|
|
- eval_batch_size: 64 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 50 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| No log | 1.0 | 346 | 0.5129 | 0.8245 | 0.5325 | 0.3537 | 0.3399 | |
|
|
| 0.5757 | 2.0 | 692 | 0.4692 | 0.8383 | 0.6238 | 0.4332 | 0.4500 | |
|
|
| 0.4598 | 3.0 | 1038 | 0.4671 | 0.8357 | 0.6235 | 0.4116 | 0.4280 | |
|
|
| 0.4598 | 4.0 | 1384 | 0.4641 | 0.8394 | 0.6756 | 0.4279 | 0.4498 | |
|
|
| 0.4567 | 5.0 | 1730 | 0.4582 | 0.8379 | 0.6325 | 0.4272 | 0.4478 | |
|
|
| 0.4499 | 6.0 | 2076 | 0.4588 | 0.8406 | 0.6718 | 0.4424 | 0.4617 | |
|
|
| 0.4499 | 7.0 | 2422 | 0.4633 | 0.8372 | 0.6655 | 0.4118 | 0.4320 | |
|
|
| 0.4517 | 8.0 | 2768 | 0.4522 | 0.8417 | 0.6340 | 0.4522 | 0.4741 | |
|
|
| 0.4477 | 9.0 | 3114 | 0.4539 | 0.8402 | 0.6644 | 0.4267 | 0.4503 | |
|
|
| 0.4477 | 10.0 | 3460 | 0.4560 | 0.8439 | 0.6645 | 0.4647 | 0.4813 | |
|
|
| 0.4508 | 11.0 | 3806 | 0.4534 | 0.8387 | 0.6499 | 0.4235 | 0.4488 | |
|
|
| 0.444 | 12.0 | 4152 | 0.4483 | 0.8432 | 0.6507 | 0.4682 | 0.4928 | |
|
|
| 0.444 | 13.0 | 4498 | 0.4501 | 0.8391 | 0.6491 | 0.4355 | 0.4633 | |
|
|
| 0.4506 | 14.0 | 4844 | 0.4532 | 0.8394 | 0.6442 | 0.4253 | 0.4490 | |
|
|
| 0.4422 | 15.0 | 5190 | 0.4528 | 0.8394 | 0.6497 | 0.4245 | 0.4494 | |
|
|
| 0.4498 | 16.0 | 5536 | 0.4663 | 0.8376 | 0.6743 | 0.4123 | 0.4332 | |
|
|
| 0.4498 | 17.0 | 5882 | 0.4476 | 0.8417 | 0.6345 | 0.4435 | 0.4672 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.1 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.0 |
|
|
|
