metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Misinformation-Covid-xlm-roberta-base
results: []
Misinformation-Covid-xlm-roberta-base
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7194
- F1: 0.4333
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-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6737 | 1.0 | 189 | 0.6662 | 0.0 |
| 0.7083 | 2.0 | 378 | 0.6540 | 0.0 |
| 0.7185 | 3.0 | 567 | 0.8346 | 0.0 |
| 0.7826 | 4.0 | 756 | 0.8685 | 0.0 |
| 0.8333 | 5.0 | 945 | 0.7939 | 0.0 |
| 0.7989 | 6.0 | 1134 | 0.8978 | 0.0 |
| 0.8009 | 7.0 | 1323 | 0.7276 | 0.3265 |
| 0.6824 | 8.0 | 1512 | 0.7733 | 0.3774 |
| 0.6979 | 9.0 | 1701 | 0.7327 | 0.4407 |
| 0.6963 | 10.0 | 1890 | 0.7194 | 0.4333 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3