electra-base-increased-bs
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: 0.3163
- Accuracy: 0.8766
- Precision: 0.8796
- Recall: 0.8726
- F1: 0.8761
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: 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 | 0.3349 | 0.8609 | 0.8673 | 0.8521 | 0.8597 |
0.3882 | 2.0 | 538 | 0.3083 | 0.8731 | 0.8747 | 0.8710 | 0.8728 |
0.3882 | 3.0 | 807 | 0.3163 | 0.8766 | 0.8796 | 0.8726 | 0.8761 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
google/electra-base-discriminator