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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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<!-- 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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# twitter-roberta-base_3epoch10.8 |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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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