metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-finetuned_ADEs_SonatafyAI
results: []
roberta-large-finetuned_ADEs_SonatafyAI
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2571
- Precision: 0.5269
- Recall: 0.6208
- F1: 0.5700
- Accuracy: 0.8859
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-07
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7192 | 1.0 | 640 | 0.3366 | 0.4491 | 0.5202 | 0.4820 | 0.8653 |
| 0.3549 | 2.0 | 1280 | 0.2814 | 0.4982 | 0.6066 | 0.5471 | 0.8803 |
| 0.3118 | 3.0 | 1920 | 0.2653 | 0.5178 | 0.6186 | 0.5637 | 0.8831 |
| 0.2827 | 4.0 | 2560 | 0.2624 | 0.5276 | 0.6372 | 0.5772 | 0.8833 |
| 0.2741 | 5.0 | 3200 | 0.2571 | 0.5269 | 0.6208 | 0.5700 | 0.8859 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1