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End of training

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README.md ADDED
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+ ---
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+ base_model: cardiffnlp/twitter-roberta-base-irony
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: twitter-roberta-base_3epoch10.8
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+ results: []
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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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+ # twitter-roberta-base_3epoch10.8
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+
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+ This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3313
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+ - Accuracy: 0.7579
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+ - F1: 0.4324
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+ - Precision: 0.6598
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+ - Recall: 0.3216
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+ - Precision Sarcastic: 0.6598
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+ - Recall Sarcastic: 0.3216
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+ - F1 Sarcastic: 0.4324
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 10
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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 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | No log | 1.0 | 347 | 2.2730 | 0.7464 | 0.4568 | 0.592 | 0.3719 | 0.592 | 0.3719 | 0.4568 |
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+ | 0.0571 | 2.0 | 694 | 1.9955 | 0.7594 | 0.3971 | 0.7051 | 0.2764 | 0.7051 | 0.2764 | 0.3971 |
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+ | 0.0756 | 3.0 | 1041 | 1.9672 | 0.7421 | 0.4526 | 0.5781 | 0.3719 | 0.5781 | 0.3719 | 0.4526 |
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+ | 0.0756 | 4.0 | 1388 | 2.0562 | 0.7493 | 0.4695 | 0.5969 | 0.3869 | 0.5969 | 0.3869 | 0.4695 |
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+ | 0.0421 | 5.0 | 1735 | 2.2045 | 0.7522 | 0.4416 | 0.6239 | 0.3417 | 0.6239 | 0.3417 | 0.4416 |
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+ | 0.0268 | 6.0 | 2082 | 2.2693 | 0.7594 | 0.4099 | 0.6905 | 0.2915 | 0.6905 | 0.2915 | 0.4099 |
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+ | 0.0268 | 7.0 | 2429 | 2.1746 | 0.7536 | 0.4466 | 0.6273 | 0.3467 | 0.6273 | 0.3467 | 0.4466 |
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+ | 0.0145 | 8.0 | 2776 | 2.3412 | 0.7550 | 0.4178 | 0.6559 | 0.3065 | 0.6559 | 0.3065 | 0.4178 |
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+ | 0.0051 | 9.0 | 3123 | 2.3512 | 0.7565 | 0.4232 | 0.6596 | 0.3116 | 0.6596 | 0.3116 | 0.4232 |
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+ | 0.0051 | 10.0 | 3470 | 2.3313 | 0.7579 | 0.4324 | 0.6598 | 0.3216 | 0.6598 | 0.3216 | 0.4324 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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