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bert-base-uncased-english-sentweet-sentiment
This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8588
- Accuracy: 0.7917
- Precision: 0.8060
- Recall: 0.7989
- F1: 0.7912
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 | 81 | 0.4525 | 0.8021 | 0.8198 | 0.8101 | 0.8014 |
| No log | 2.0 | 162 | 0.5388 | 0.7847 | 0.8076 | 0.7939 | 0.7835 |
| No log | 3.0 | 243 | 0.5883 | 0.7917 | 0.8233 | 0.8023 | 0.7897 |
| No log | 4.0 | 324 | 0.5507 | 0.7778 | 0.7917 | 0.7849 | 0.7773 |
| No log | 5.0 | 405 | 0.7801 | 0.7847 | 0.7922 | 0.7900 | 0.7846 |
| No log | 6.0 | 486 | 0.8588 | 0.7917 | 0.8060 | 0.7989 | 0.7912 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.1+cu117
- Datasets 2.6.1
- Tokenizers 0.11.0
