|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: roberta-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- f1 |
|
|
- precision |
|
|
- recall |
|
|
model-index: |
|
|
- name: roberta-large-ToM6 |
|
|
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. --> |
|
|
|
|
|
# roberta-large-ToM6 |
|
|
|
|
|
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.2003 |
|
|
- Accuracy: 0.9368 |
|
|
- F1: 0.9060 |
|
|
- Precision: 0.9298 |
|
|
- Recall: 0.8833 |
|
|
|
|
|
## 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: 2015 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 5 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
|
|
| 0.6542 | 1.0 | 93 | 0.3393 | 0.8846 | 0.8696 | 0.7895 | 0.9677 | |
|
|
| 0.2542 | 2.0 | 186 | 0.2763 | 0.9359 | 0.9231 | 0.8824 | 0.9677 | |
|
|
| 0.1448 | 3.0 | 279 | 0.3087 | 0.8718 | 0.8571 | 0.7692 | 0.9677 | |
|
|
| 0.1303 | 4.0 | 372 | 0.2598 | 0.9487 | 0.9355 | 0.9355 | 0.9355 | |
|
|
| 0.0777 | 5.0 | 465 | 0.3035 | 0.9487 | 0.9355 | 0.9355 | 0.9355 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.56.0 |
|
|
- Pytorch 2.8.0+cu126 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.22.0 |
|
|
|
