metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: multipride_umberto_ner
results: []
multipride_umberto_ner
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2343
- Accuracy: 0.9325
- Precision: 0.9026
- Recall: 0.8719
- F1: 0.8862
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: 8
- eval_batch_size: 8
- seed: 42
- 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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.491 | 1.0 | 95 | 0.3350 | 0.9018 | 0.9459 | 0.7419 | 0.7975 |
| 0.2737 | 2.0 | 190 | 0.3016 | 0.9080 | 0.8771 | 0.8074 | 0.8360 |
| 0.2221 | 3.0 | 285 | 0.3218 | 0.8896 | 0.8137 | 0.9071 | 0.8456 |
| 0.2015 | 4.0 | 380 | 0.2428 | 0.9264 | 0.8805 | 0.8805 | 0.8805 |
| 0.1783 | 5.0 | 475 | 0.2343 | 0.9325 | 0.9026 | 0.8719 | 0.8862 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1