metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: RoBERTa-THESIS
results: []
RoBERTa-THESIS
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1698
- F1: 0.7701
- Recall: 0.7701
- Accuracy: 0.7701
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
|---|---|---|---|---|---|---|
| 0.9918 | 1.0 | 1446 | 0.8174 | 0.7433 | 0.7433 | 0.7433 |
| 0.7223 | 2.0 | 2892 | 0.7799 | 0.7618 | 0.7618 | 0.7618 |
| 0.5389 | 3.0 | 4338 | 0.7730 | 0.7716 | 0.7716 | 0.7716 |
| 0.4073 | 4.0 | 5784 | 0.8121 | 0.7737 | 0.7737 | 0.7737 |
| 0.2985 | 5.0 | 7230 | 0.8841 | 0.7697 | 0.7697 | 0.7697 |
| 0.2233 | 6.0 | 8676 | 0.9573 | 0.7717 | 0.7717 | 0.7717 |
| 0.1679 | 7.0 | 10122 | 1.0132 | 0.7721 | 0.7721 | 0.7721 |
| 0.1233 | 8.0 | 11568 | 1.0948 | 0.7691 | 0.7691 | 0.7691 |
| 0.096 | 9.0 | 13014 | 1.1502 | 0.7689 | 0.7689 | 0.7689 |
| 0.0799 | 10.0 | 14460 | 1.1698 | 0.7701 | 0.7701 | 0.7701 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3