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twitter-data-xlm-roberta-base-eng-only-sentiment-finetuned-memes
This model is a fine-tuned version of jayantapaul888/twitter-data-xlm-roberta-base-sentiment-finetuned-memes on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6286
- Accuracy: 0.8660
- Precision: 0.8796
- Recall: 0.8795
- F1: 0.8795
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 378 | 0.3421 | 0.8407 | 0.8636 | 0.8543 | 0.8553 |
| 0.396 | 2.0 | 756 | 0.3445 | 0.8496 | 0.8726 | 0.8634 | 0.8631 |
| 0.2498 | 3.0 | 1134 | 0.3656 | 0.8585 | 0.8764 | 0.8727 | 0.8723 |
| 0.1543 | 4.0 | 1512 | 0.4549 | 0.8600 | 0.8742 | 0.8740 | 0.8741 |
| 0.1543 | 5.0 | 1890 | 0.5932 | 0.8645 | 0.8783 | 0.8780 | 0.8780 |
| 0.0815 | 6.0 | 2268 | 0.6286 | 0.8660 | 0.8796 | 0.8795 | 0.8795 |
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1
