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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: Twroberta-baseB_10epoch |
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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_10epoch |
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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: 0.1763 |
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- Accuracy: 0.7771 |
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- Precision: 0.2366 |
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- Recall: 0.3137 |
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- F1: 0.2679 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 217 | 0.1251 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 434 | 0.1213 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1617 | 3.0 | 651 | 0.1226 | 0.8157 | 0.2655 | 0.3026 | 0.2828 | |
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| 0.1617 | 4.0 | 868 | 0.1423 | 0.7671 | 0.1991 | 0.2989 | 0.2389 | |
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| 0.0899 | 5.0 | 1085 | 0.1594 | 0.7364 | 0.2142 | 0.3727 | 0.2695 | |
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| 0.0899 | 6.0 | 1302 | 0.1560 | 0.8086 | 0.2567 | 0.2214 | 0.2320 | |
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| 0.0411 | 7.0 | 1519 | 0.1963 | 0.715 | 0.1945 | 0.3875 | 0.2584 | |
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| 0.0411 | 8.0 | 1736 | 0.1687 | 0.7914 | 0.2520 | 0.2804 | 0.2601 | |
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| 0.0411 | 9.0 | 1953 | 0.1726 | 0.7843 | 0.2419 | 0.2989 | 0.2646 | |
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| 0.0197 | 10.0 | 2170 | 0.1763 | 0.7771 | 0.2366 | 0.3137 | 0.2679 | |
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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 2.19.2 |
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- Tokenizers 0.19.1 |
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