nlpClassifier
This model is a fine-tuned version of distilroberta-base on the glue and the mrpc datasets. It achieves the following results on the evaluation set:
- Loss: 0.8137
- Accuracy: 0.8382
- F1: 0.8874
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | F1 |
---|---|---|---|---|---|
0.4111 | 1.0893 | 500 | 0.8351 | 0.8260 | 0.8743 |
0.2926 | 2.1786 | 1000 | 0.8137 | 0.8382 | 0.8874 |
0.1521 | 3.2680 | 1500 | 0.9311 | 0.8333 | 0.8851 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for Davalejo/nlpClassifier
Base model
distilbert/distilroberta-base