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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: ec_classfication_0502_google_electra_base_discriminator |
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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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# ec_classfication_0502_google_electra_base_discriminator |
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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: 0.8369 |
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- F1: 0.8511 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 59 | 0.6505 | 0.3934 | |
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| No log | 2.0 | 118 | 0.4319 | 0.8211 | |
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| No log | 3.0 | 177 | 0.4704 | 0.8269 | |
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| No log | 4.0 | 236 | 0.4700 | 0.8571 | |
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| No log | 5.0 | 295 | 0.5886 | 0.8478 | |
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| No log | 6.0 | 354 | 0.8250 | 0.8 | |
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| No log | 7.0 | 413 | 0.6282 | 0.8571 | |
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| No log | 8.0 | 472 | 0.6684 | 0.8632 | |
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| 0.2241 | 9.0 | 531 | 0.7479 | 0.8632 | |
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| 0.2241 | 10.0 | 590 | 0.8523 | 0.8387 | |
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| 0.2241 | 11.0 | 649 | 0.7993 | 0.8511 | |
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| 0.2241 | 12.0 | 708 | 0.8075 | 0.8602 | |
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| 0.2241 | 13.0 | 767 | 0.8326 | 0.8511 | |
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| 0.2241 | 14.0 | 826 | 0.8350 | 0.8511 | |
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| 0.2241 | 15.0 | 885 | 0.8369 | 0.8511 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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