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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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- 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-discriminator-english-sentweet-profane
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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-english-sentweet-profane
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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: 0.6382
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- Accuracy: 0.8125
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- Precision: 0.8271
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- Recall: 0.8236
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- F1: 0.8124
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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: 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: 6
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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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| No log | 1.0 | 81 | 0.5327 | 0.7847 | 0.7879 | 0.7904 | 0.7846 |
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| No log | 2.0 | 162 | 0.4762 | 0.8229 | 0.8347 | 0.8330 | 0.8229 |
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| No log | 3.0 | 243 | 0.4884 | 0.8194 | 0.8363 | 0.8314 | 0.8193 |
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| No log | 4.0 | 324 | 0.4166 | 0.8021 | 0.8059 | 0.8083 | 0.8020 |
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| No log | 5.0 | 405 | 0.5227 | 0.8090 | 0.8171 | 0.8175 | 0.8090 |
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| No log | 6.0 | 486 | 0.6382 | 0.8125 | 0.8271 | 0.8236 | 0.8124 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.13.1+cu117
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- Datasets 2.6.1
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- Tokenizers 0.11.0
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