sentence_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: 0.2690
- F1-score: 0.9132
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 |
|---|---|---|---|---|
| 0.3365 | 1.0 | 2500 | 0.3218 | 0.9066 |
| 0.2477 | 2.0 | 5000 | 0.2690 | 0.9132 |
| 0.1417 | 3.0 | 7500 | 0.3876 | 0.9178 |
| 0.0645 | 4.0 | 10000 | 0.4436 | 0.9216 |
| 0.0304 | 5.0 | 12500 | 0.5194 | 0.9208 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for Jedida/sentence_sentiments_analysis_bert
Base model
google-bert/bert-base-cased