electra-base-increased-bs-lr
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3120
- Accuracy: 0.8919
- Precision: 0.8962
- Recall: 0.8865
- F1: 0.8913
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 269 | 0.3037 | 0.8748 | 0.8840 | 0.8627 | 0.8732 |
0.3324 | 2.0 | 538 | 0.2916 | 0.8896 | 0.8942 | 0.8838 | 0.8890 |
0.3324 | 3.0 | 807 | 0.3120 | 0.8919 | 0.8962 | 0.8865 | 0.8913 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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