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--- |
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license: apache-2.0 |
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base_model: google/electra-base-discriminator |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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model-index: |
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- name: electra-base-discriminator-finetuned-detests |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# electra-base-discriminator-finetuned-detests |
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1215 |
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- Accuracy: 0.7807 |
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- F1-score: 0.7308 |
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- Precision: 0.7162 |
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- Recall: 0.7768 |
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- Auc: 0.7768 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| |
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| 0.3236 | 1.0 | 174 | 0.4661 | 0.7610 | 0.6684 | 0.6647 | 0.6728 | 0.6728 | |
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| 0.3239 | 2.0 | 348 | 0.4287 | 0.7987 | 0.7144 | 0.7138 | 0.7149 | 0.7149 | |
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| 0.3421 | 3.0 | 522 | 0.5586 | 0.7741 | 0.7292 | 0.7163 | 0.7853 | 0.7853 | |
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| 0.2288 | 4.0 | 696 | 0.6229 | 0.7807 | 0.7308 | 0.7162 | 0.7768 | 0.7768 | |
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| 0.1888 | 5.0 | 870 | 0.6629 | 0.7954 | 0.7293 | 0.7173 | 0.7483 | 0.7483 | |
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| 0.2205 | 6.0 | 1044 | 0.8462 | 0.8036 | 0.7349 | 0.7251 | 0.7485 | 0.7485 | |
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| 0.1512 | 7.0 | 1218 | 0.8362 | 0.8151 | 0.7335 | 0.7367 | 0.7306 | 0.7306 | |
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| 0.2345 | 8.0 | 1392 | 1.0372 | 0.7758 | 0.7204 | 0.7063 | 0.7584 | 0.7584 | |
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| 0.0592 | 9.0 | 1566 | 1.0396 | 0.7840 | 0.7291 | 0.7142 | 0.7663 | 0.7663 | |
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| 0.0381 | 10.0 | 1740 | 1.1215 | 0.7807 | 0.7308 | 0.7162 | 0.7768 | 0.7768 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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