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bert-finetuned-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: 1.4884
- Accuracy: 0.7698
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
---|---|---|---|---|
0.6778 | 1.0 | 722 | 0.7149 | 0.7482 |
0.3768 | 2.0 | 1444 | 0.9821 | 0.7410 |
0.1612 | 3.0 | 2166 | 1.4027 | 0.7662 |
0.094 | 4.0 | 2888 | 1.4884 | 0.7698 |
0.0448 | 5.0 | 3610 | 1.6463 | 0.7590 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1