metadata
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MulderFinders
results: []
MulderFinders
This model is a fine-tuned version of EuroBERT/EuroBERT-210m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 1.0
- F1 Score: 1.0
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: 32
- seed: 69
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.1365 | 0.3030 | 20 | 0.0282 | 0.9924 | 0.9927 |
| 0.0633 | 0.6061 | 40 | 0.1290 | 0.9773 | 0.9774 |
| 0.0362 | 0.9091 | 60 | 0.0390 | 0.9962 | 0.9963 |
| 0.0271 | 1.2121 | 80 | 0.0284 | 0.9962 | 0.9963 |
| 0.0001 | 1.5152 | 100 | 0.0079 | 0.9962 | 0.9963 |
| 0.0026 | 1.8182 | 120 | 0.0322 | 0.9962 | 0.9963 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2