DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_NULL_second_train_set_null_False
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0557
- Precision: 0.9930
- Recall: 0.9878
- F1: 0.9904
- Accuracy: 0.9814
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 479 | 0.3334 | 0.9041 | 0.9041 | 0.9041 | 0.8550 |
0.3756 | 2.0 | 958 | 0.3095 | 0.8991 | 0.9251 | 0.9119 | 0.8649 |
0.2653 | 3.0 | 1437 | 0.3603 | 0.8929 | 0.9527 | 0.9218 | 0.8779 |
0.1991 | 4.0 | 1916 | 0.3907 | 0.8919 | 0.9540 | 0.9219 | 0.8779 |
0.1586 | 5.0 | 2395 | 0.3642 | 0.9070 | 0.9356 | 0.9211 | 0.8788 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
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