sentiment_v2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4845
- Accuracy: 0.8511
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.583 | 1.0 | 3410 | 0.5539 | 0.7994 |
| 0.4415 | 2.0 | 6820 | 0.5131 | 0.8268 |
| 0.3368 | 3.0 | 10230 | 0.4683 | 0.8497 |
| 0.2845 | 4.0 | 13640 | 0.4845 | 0.8511 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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distilbert/distilbert-base-uncased
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