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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: Twroberta-baseB_5epoch |
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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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# Twroberta-baseB_5epoch |
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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: 0.1520 |
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- Accuracy: 0.7793 |
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- F1: 0.2545 |
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- Precision: 0.2289 |
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- Recall: 0.2878 |
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- Precision Sarcastic: 0.3258 |
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- Recall Sarcastic: 0.4 |
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- F1 Sarcastic: 0.3591 |
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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: 16 |
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- eval_batch_size: 16 |
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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 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:| |
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| No log | 1.0 | 217 | 0.1224 | 0.8571 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 434 | 0.1224 | 0.8686 | 0.2294 | 0.4139 | 0.1587 | 0.6232 | 0.2389 | 0.3454 | |
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| 0.1581 | 3.0 | 651 | 0.1277 | 0.7979 | 0.2474 | 0.2290 | 0.2694 | 0.3380 | 0.4 | 0.3664 | |
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| 0.1581 | 4.0 | 868 | 0.1438 | 0.7914 | 0.2503 | 0.2424 | 0.2620 | 0.3137 | 0.3556 | 0.3333 | |
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| 0.0781 | 5.0 | 1085 | 0.1520 | 0.7793 | 0.2545 | 0.2289 | 0.2878 | 0.3258 | 0.4 | 0.3591 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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