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--- |
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license: apache-2.0 |
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base_model: google/electra-small-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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model-index: |
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- name: electra-small-discriminator-zeroshot-v1.1-none |
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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-small-discriminator-zeroshot-v1.1-none |
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This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3747 |
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- F1 Macro: 0.4125 |
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- F1 Micro: 0.4620 |
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- Accuracy Balanced: 0.4701 |
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- Accuracy: 0.4620 |
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- Precision Macro: 0.5162 |
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- Recall Macro: 0.4701 |
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- Precision Micro: 0.4620 |
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- Recall Micro: 0.4620 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 80085 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.04 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| |
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| 0.4765 | 0.32 | 5000 | 0.5300 | 0.7326 | 0.7528 | 0.7329 | 0.7528 | 0.7322 | 0.7329 | 0.7528 | 0.7528 | |
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| 0.4408 | 0.65 | 10000 | 0.5099 | 0.7402 | 0.765 | 0.7359 | 0.765 | 0.7463 | 0.7359 | 0.765 | 0.765 | |
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| 0.4169 | 0.97 | 15000 | 0.4976 | 0.7473 | 0.7702 | 0.7439 | 0.7702 | 0.7517 | 0.7439 | 0.7702 | 0.7702 | |
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| 0.387 | 1.3 | 20000 | 0.4943 | 0.7525 | 0.7742 | 0.7498 | 0.7742 | 0.7559 | 0.7498 | 0.7742 | 0.7742 | |
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| 0.3905 | 1.62 | 25000 | 0.4931 | 0.7522 | 0.775 | 0.7484 | 0.775 | 0.7572 | 0.7484 | 0.775 | 0.775 | |
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| 0.4001 | 1.95 | 30000 | 0.4924 | 0.7544 | 0.7752 | 0.7524 | 0.7752 | 0.7568 | 0.7524 | 0.7752 | 0.7752 | |
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| 0.3995 | 2.27 | 35000 | 0.4900 | 0.7543 | 0.7758 | 0.7517 | 0.7758 | 0.7576 | 0.7517 | 0.7758 | 0.7758 | |
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| 0.3981 | 2.6 | 40000 | 0.4906 | 0.7529 | 0.7742 | 0.7504 | 0.7742 | 0.7558 | 0.7504 | 0.7742 | 0.7742 | |
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| 0.4232 | 2.92 | 45000 | 0.4904 | 0.7544 | 0.776 | 0.7516 | 0.776 | 0.7579 | 0.7516 | 0.776 | 0.776 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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