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sentiment-roberta-e2-b16-v2-w0.01
This model is a fine-tuned version of siebert/sentiment-roberta-large-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8630
- F1: 0.7520
- Recall: 0.7520
- Precision: 0.7520
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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Precision |
---|---|---|---|---|---|---|
No log | 1.0 | 375 | 0.8651 | 0.6739 | 0.6739 | 0.6739 |
0.6564 | 2.0 | 750 | 0.8630 | 0.7520 | 0.7520 | 0.7520 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3