metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta_echr_truncated_facts_all_labels
results: []
library_name: transformers
roberta_echr_truncated_facts_all_labels
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0674
- F1: 0.7452
- Roc Auc: 0.8460
- Accuracy: 0.5883
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0835 | 1.0 | 1765 | 0.0780 | 0.6933 | 0.7942 | 0.5214 |
| 0.0674 | 2.0 | 3530 | 0.0699 | 0.7375 | 0.8363 | 0.5577 |
| 0.0584 | 3.0 | 5295 | 0.0674 | 0.7452 | 0.8460 | 0.5883 |
| 0.0474 | 4.0 | 7060 | 0.0690 | 0.7372 | 0.8448 | 0.5787 |
| 0.04 | 5.0 | 8825 | 0.0695 | 0.7429 | 0.8475 | 0.5870 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.15.1