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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: electra-base-discriminator_roberta-base |
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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_roberta-base |
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4180 |
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- Accuracy: 0.8768 |
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- F1: 0.8767 |
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- Precision: 0.8766 |
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- Recall: 0.8768 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.955 | 1.0 | 91 | 0.8849 | 0.6349 | 0.5849 | 0.6173 | 0.6349 | |
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| 0.4845 | 2.0 | 182 | 0.4777 | 0.8237 | 0.8221 | 0.8271 | 0.8237 | |
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| 0.3434 | 3.0 | 273 | 0.3821 | 0.8580 | 0.8579 | 0.8598 | 0.8580 | |
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| 0.2683 | 4.0 | 364 | 0.5158 | 0.8237 | 0.8213 | 0.8362 | 0.8237 | |
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| 0.1675 | 5.0 | 455 | 0.3875 | 0.8643 | 0.8633 | 0.8651 | 0.8643 | |
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| 0.1788 | 6.0 | 546 | 0.4180 | 0.8768 | 0.8767 | 0.8766 | 0.8768 | |
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| 0.1669 | 7.0 | 637 | 0.4189 | 0.8768 | 0.8754 | 0.8775 | 0.8768 | |
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| 0.1103 | 8.0 | 728 | 0.5338 | 0.8534 | 0.8542 | 0.8569 | 0.8534 | |
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| 0.1597 | 9.0 | 819 | 0.4306 | 0.8674 | 0.8674 | 0.8676 | 0.8674 | |
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| 0.1443 | 10.0 | 910 | 0.6446 | 0.8580 | 0.8574 | 0.8580 | 0.8580 | |
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| 0.1012 | 11.0 | 1001 | 0.5104 | 0.8534 | 0.8535 | 0.8541 | 0.8534 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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