<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
tweet_sentiments_analysis_bert
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6413
- F1-score: 0.7292
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: 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 |
|---|---|---|---|---|
| 0.7027 | 1.0 | 1000 | 0.6758 | 0.6903 |
| 0.5666 | 2.0 | 2000 | 0.6413 | 0.7292 |
| 0.4067 | 3.0 | 3000 | 0.8208 | 0.7379 |
| 0.2546 | 4.0 | 4000 | 1.1904 | 0.7401 |
| 0.1256 | 5.0 | 5000 | 1.4513 | 0.7377 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
