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update model card README.md

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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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+
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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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+
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+ # distilbert-base-uncased-finetuned-tweet_hate
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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