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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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datasets: |
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- tweet_eval |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased-finetuned-tweet_hate |
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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: tweet_eval |
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type: tweet_eval |
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args: hate |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.77 |
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- name: F1 |
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type: f1 |
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value: 0.7711956429754464 |
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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-tweet_hate |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6390 |
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- Accuracy: 0.77 |
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- F1: 0.7712 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.5003 | 1.0 | 282 | 0.4716 | 0.76 | 0.7613 | |
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| 0.3428 | 2.0 | 564 | 0.4767 | 0.771 | 0.7721 | |
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| 0.2559 | 3.0 | 846 | 0.5256 | 0.778 | 0.7789 | |
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| 0.1811 | 4.0 | 1128 | 0.5839 | 0.774 | 0.7748 | |
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| 0.134 | 5.0 | 1410 | 0.6390 | 0.77 | 0.7712 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 1.16.1 |
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- Tokenizers 0.15.0 |
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