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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-uncased |
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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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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: distilbert-base-uncased-finetuned_on_hata_dateset |
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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: 0.9178338001867413 |
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- name: F1 |
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type: f1 |
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value: 0.9154943774479662 |
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- name: Recall |
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type: recall |
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value: 0.9178338001867413 |
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- name: Precision |
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type: precision |
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value: 0.9137800286953446 |
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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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# distilbert-base-uncased-finetuned_on_hata_dateset |
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the hate_speech18 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0451 |
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- Accuracy: 0.9178 |
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- F1: 0.9155 |
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- Recall: 0.9178 |
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- Precision: 0.9138 |
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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: 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 0.3342 | 1.0 | 268 | 0.3774 | 0.8497 | 0.8702 | 0.8497 | 0.9131 | |
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| 0.2411 | 2.0 | 536 | 0.4330 | 0.9020 | 0.9097 | 0.9020 | 0.9237 | |
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| 0.1374 | 3.0 | 804 | 0.5690 | 0.8964 | 0.9050 | 0.8964 | 0.9206 | |
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| 0.0804 | 4.0 | 1072 | 1.0798 | 0.9188 | 0.9140 | 0.9188 | 0.9117 | |
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| 0.0428 | 5.0 | 1340 | 1.0451 | 0.9178 | 0.9155 | 0.9178 | 0.9138 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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