|
|
--- |
|
|
base_model: microsoft/deberta-v3-large |
|
|
library_name: transformers |
|
|
license: mit |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: panclef_data_deberta_finetuned |
|
|
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. --> |
|
|
|
|
|
# panclef_data_deberta_finetuned |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the PAN CLEF 2025 dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1185 |
|
|
- Accuracy: 0.9728 |
|
|
- Precision: 0.9735 |
|
|
- Recall: 0.9728 |
|
|
- F1: 0.9729 |
|
|
|
|
|
## 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: 3e-05 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 10 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
|
| 0.3364 | 1.0 | 556 | 0.1755 | 0.9550 | 0.9572 | 0.9550 | 0.9552 | |
|
|
| 0.2607 | 2.0 | 1112 | 0.2262 | 0.9347 | 0.9379 | 0.9347 | 0.9337 | |
|
|
| 0.1895 | 3.0 | 1668 | 0.1562 | 0.9592 | 0.9619 | 0.9592 | 0.9595 | |
|
|
| 0.1558 | 4.0 | 2224 | 0.1673 | 0.9627 | 0.9632 | 0.9627 | 0.9625 | |
|
|
| 0.1617 | 5.0 | 2780 | 0.1505 | 0.9657 | 0.9659 | 0.9657 | 0.9658 | |
|
|
| 0.1394 | 6.0 | 3336 | 0.1359 | 0.9632 | 0.9657 | 0.9632 | 0.9635 | |
|
|
| 0.1354 | 7.0 | 3892 | 0.1310 | 0.9725 | 0.9725 | 0.9725 | 0.9725 | |
|
|
| 0.1192 | 8.0 | 4448 | 0.1238 | 0.9683 | 0.9699 | 0.9683 | 0.9685 | |
|
|
| 0.1096 | 9.0 | 5004 | 0.1222 | 0.9742 | 0.9744 | 0.9742 | 0.9742 | |
|
|
| 0.1127 | 10.0 | 5560 | 0.1185 | 0.9728 | 0.9735 | 0.9728 | 0.9729 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.45.2 |
|
|
- Pytorch 2.4.1 |
|
|
- Datasets 3.0.0 |
|
|
- Tokenizers 0.20.1 |
|
|
|
