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README.md
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---
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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: bertweet-base-finetuned-SARC-combined-DS
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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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# bertweet-base-finetuned-SARC-combined-DS
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This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4624
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- Accuracy: 0.7611
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- Precision: 0.7611
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- Recall: 0.7611
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- F1: 0.7611
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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: 1e-05
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- train_batch_size: 64
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- eval_batch_size: 16
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- seed: 43
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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: 30
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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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| 0.4319 | 4.0 | 44819 | 0.5049 | 0.7790 | 0.7796 | 0.7789 | 0.7789 |
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| 0.2835 | 8.0 | 89638 | 0.6475 | 0.7663 | 0.7664 | 0.7663 | 0.7663 |
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| 0.1797 | 12.0 | 134457 | 0.8746 | 0.7638 | 0.7639 | 0.7637 | 0.7637 |
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| 0.1219 | 16.0 | 179276 | 1.0595 | 0.7585 | 0.7597 | 0.7587 | 0.7583 |
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| 0.0905 | 20.0 | 224095 | 1.2115 | 0.7611 | 0.7612 | 0.7612 | 0.7611 |
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| 0.0728 | 24.0 | 268914 | 1.3644 | 0.7628 | 0.7629 | 0.7627 | 0.7627 |
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| 0.0612 | 28.0 | 313733 | 1.4624 | 0.7611 | 0.7611 | 0.7611 | 0.7611 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.10.1+cu111
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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