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--- |
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license: apache-2.0 |
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base_model: agvidit1/GoogleTinyBert_HateSpeech_pretrain |
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tags: |
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- generated_from_trainer |
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datasets: |
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- hate_speech18 |
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metrics: |
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- accuracy |
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model-index: |
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- name: berttiny-hate_speech18-bothpretrained |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: hate_speech18 |
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type: hate_speech18 |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.879798903107861 |
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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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# berttiny-hate_speech18-bothpretrained |
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This model is a fine-tuned version of [agvidit1/GoogleTinyBert_HateSpeech_pretrain](https://huggingface.co/agvidit1/GoogleTinyBert_HateSpeech_pretrain) on the hate_speech18 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4682 |
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- Accuracy: 0.8798 |
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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: 7.12739424754752e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 128 |
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- seed: 34 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.4804 | 1.0 | 479 | 0.4778 | 0.8624 | |
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| 0.4592 | 2.0 | 958 | 0.4688 | 0.8761 | |
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| 0.4471 | 3.0 | 1437 | 0.4681 | 0.8780 | |
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| 0.4405 | 4.0 | 1916 | 0.4682 | 0.8798 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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