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electra-base-discriminator-finetuned-removed-0530
This model is a fine-tuned version of google/electra-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9713
- Accuracy: 0.8824
- F1: 0.8824
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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 3180 | 0.6265 | 0.8107 | 0.8128 |
No log | 2.0 | 6360 | 0.5158 | 0.8544 | 0.8541 |
No log | 3.0 | 9540 | 0.6686 | 0.8563 | 0.8567 |
No log | 4.0 | 12720 | 0.6491 | 0.8711 | 0.8709 |
No log | 5.0 | 15900 | 0.8048 | 0.8660 | 0.8672 |
No log | 6.0 | 19080 | 0.8110 | 0.8708 | 0.8710 |
No log | 7.0 | 22260 | 1.0082 | 0.8651 | 0.8640 |
0.2976 | 8.0 | 25440 | 0.8343 | 0.8811 | 0.8814 |
0.2976 | 9.0 | 28620 | 0.9366 | 0.8780 | 0.8780 |
0.2976 | 10.0 | 31800 | 0.9713 | 0.8824 | 0.8824 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.12.1