metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-large-finetuned-ours-DS
results: []
roberta-large-finetuned-ours-DS
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8358
- Accuracy: 0.71
- Precision: 0.6611
- Recall: 0.6691
- F1: 0.6570
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
1.0561 | 0.99 | 99 | 0.8773 | 0.615 | 0.4054 | 0.5584 | 0.4591 |
0.762 | 1.98 | 198 | 0.6514 | 0.715 | 0.6735 | 0.6672 | 0.6588 |
0.5661 | 2.97 | 297 | 0.6806 | 0.71 | 0.6764 | 0.6608 | 0.6435 |
0.3699 | 3.96 | 396 | 0.8358 | 0.71 | 0.6611 | 0.6691 | 0.6570 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1