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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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- f1 |
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model-index: |
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- name: electra-base-fp16 |
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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-fp16 |
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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: 0.3364 |
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- Accuracy: 0.8873 |
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- Precision: 0.8903 |
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- Recall: 0.8835 |
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- F1: 0.8869 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.3204 | 1.0 | 1074 | 0.2991 | 0.8777 | 0.8868 | 0.8660 | 0.8763 | |
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| 0.2293 | 2.0 | 2148 | 0.3006 | 0.8884 | 0.8926 | 0.8832 | 0.8879 | |
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| 0.1761 | 3.0 | 3222 | 0.3364 | 0.8873 | 0.8903 | 0.8835 | 0.8869 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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