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DistilBERTFINAL_ctxSentence_TRAIN_essays_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: 0.7680
- Precision: 0.9838
- Recall: 0.6632
- F1: 0.7923
- Accuracy: 0.6624
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 | 130 | 0.2980 | 0.9315 | 0.9533 | 0.9423 | 0.9081 |
No log | 2.0 | 260 | 0.2053 | 0.9537 | 0.9626 | 0.9581 | 0.9338 |
No log | 3.0 | 390 | 0.1873 | 0.9464 | 0.9907 | 0.9680 | 0.9485 |
0.3064 | 4.0 | 520 | 0.1811 | 0.9585 | 0.9720 | 0.9652 | 0.9449 |
0.3064 | 5.0 | 650 | 0.1887 | 0.9587 | 0.9766 | 0.9676 | 0.9485 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3