metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-detect-dep-v2
results: []
roberta-large-detect-dep-v2
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7719
- Accuracy: 0.691
- F1: 0.7625
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-06
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6278 | 1.0 | 751 | 0.5546 | 0.763 | 0.8227 |
| 0.5472 | 2.0 | 1502 | 0.5449 | 0.743 | 0.8160 |
| 0.4787 | 3.0 | 2253 | 0.5744 | 0.72 | 0.7929 |
| 0.423 | 4.0 | 3004 | 0.7290 | 0.702 | 0.7799 |
| 0.3803 | 5.0 | 3755 | 0.7719 | 0.691 | 0.7625 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3