bert-base-multilingual-cased-finetuned-twitter_sentiment
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0045
- F1-score: 0.9985
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: 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 | F1-score |
|---|---|---|---|---|
| 0.1961 | 1.0 | 1080 | 0.0873 | 0.9819 |
| 0.0918 | 2.0 | 2160 | 0.0252 | 0.9935 |
| 0.0737 | 3.0 | 3240 | 0.0073 | 0.9985 |
| 0.0298 | 4.0 | 4320 | 0.0087 | 0.9981 |
| 0.01 | 5.0 | 5400 | 0.0045 | 0.9985 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for Gerti/bert-base-multilingual-cased-finetuned-twitter_sentiment
Base model
google-bert/bert-base-multilingual-cased