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: 0.5841
- F1-score: 0.7663
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 |
|---|---|---|---|---|
| 0.6679 | 1.0 | 1000 | 0.6750 | 0.7263 |
| 0.5466 | 2.0 | 2000 | 0.5841 | 0.7663 |
| 0.3779 | 3.0 | 3000 | 0.8963 | 0.7708 |
| 0.233 | 4.0 | 4000 | 1.1329 | 0.7681 |
| 0.12 | 5.0 | 5000 | 1.3381 | 0.7677 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
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Model tree for Jedida/tweet_sentiments_analysis_bert
Base model
google-bert/bert-base-cased