metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: cnnroberta
results: []
cnnroberta
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7735
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
- Accuracy: 0.7446
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 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5531 | 1.0 | 583 | 0.7817 | 0.0 | 0.0 | 0.0 | 0.7332 |
| 0.5727 | 2.0 | 1166 | 0.6993 | 0.0 | 0.0 | 0.0 | 0.7660 |
| 0.5215 | 3.0 | 1749 | 0.7671 | 0.0 | 0.0 | 0.0 | 0.7416 |
| 0.4454 | 4.0 | 2332 | 0.7735 | 0.0 | 0.0 | 0.0 | 0.7446 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0