sentiment-analysis-twitter
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the new_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4579
- Accuracy: 0.7965
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5315 | 1.0 | 157 | 0.4517 | 0.788 |
0.388 | 2.0 | 314 | 0.4416 | 0.8 |
0.3307 | 3.0 | 471 | 0.4579 | 0.7965 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1
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