|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: EuroBERT/EuroBERT-210m |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: eurobert_Eau |
|
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. --> |
|
|
|
# eurobert_Eau |
|
|
|
This model is a fine-tuned version of [EuroBERT/EuroBERT-210m](https://huggingface.co/EuroBERT/EuroBERT-210m) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1286 |
|
- Accuracy: 0.9508 |
|
- F1: 0.9491 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- 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 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.8035 | 1.0 | 67 | 0.4268 | 0.8809 | 0.8836 | |
|
| 0.3476 | 2.0 | 134 | 0.2320 | 0.9168 | 0.9174 | |
|
| 0.263 | 3.0 | 201 | 0.2839 | 0.9031 | 0.9010 | |
|
| 0.2119 | 4.0 | 268 | 0.1522 | 0.9385 | 0.9393 | |
|
| 0.191 | 5.0 | 335 | 0.1765 | 0.9314 | 0.9296 | |
|
| 0.1797 | 6.0 | 402 | 0.1228 | 0.9480 | 0.9474 | |
|
| 0.1639 | 7.0 | 469 | 0.1065 | 0.9485 | 0.9500 | |
|
| 0.1422 | 8.0 | 536 | 0.1347 | 0.9428 | 0.9423 | |
|
| 0.1237 | 9.0 | 603 | 0.1047 | 0.9504 | 0.9510 | |
|
| 0.1119 | 10.0 | 670 | 0.1286 | 0.9508 | 0.9491 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.3 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.3.2 |
|
- Tokenizers 0.21.0 |
|
|
