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bertweet-base-finetuned-SARC-DS

Text Classification
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PyTorch
roberta
Generated from Trainer
Inference Endpoints
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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-DS
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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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+ # bertweet-base-finetuned-SARC-DS
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+
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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: 1.7094
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+ - Accuracy: 0.7636
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+ - Precision: 0.7637
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+ - Recall: 0.7636
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+ - F1: 0.7636
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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: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 32
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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: 20
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.4978 | 1.0 | 44221 | 0.4899 | 0.7777 | 0.7787 | 0.7778 | 0.7775 |
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+ | 0.4413 | 2.0 | 88442 | 0.4833 | 0.7798 | 0.7803 | 0.7798 | 0.7797 |
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+ | 0.3943 | 3.0 | 132663 | 0.5387 | 0.7784 | 0.7784 | 0.7784 | 0.7784 |
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+ | 0.3461 | 4.01 | 176884 | 0.6184 | 0.7690 | 0.7701 | 0.7690 | 0.7688 |
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+ | 0.3024 | 5.01 | 221105 | 0.6899 | 0.7684 | 0.7691 | 0.7684 | 0.7682 |
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+ | 0.2653 | 6.01 | 265326 | 0.7805 | 0.7654 | 0.7660 | 0.7654 | 0.7653 |
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+ | 0.2368 | 7.01 | 309547 | 0.9066 | 0.7643 | 0.7648 | 0.7643 | 0.7642 |
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+ | 0.2166 | 8.01 | 353768 | 1.0548 | 0.7612 | 0.7620 | 0.7611 | 0.7610 |
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+ | 0.2005 | 9.01 | 397989 | 1.0649 | 0.7639 | 0.7639 | 0.7639 | 0.7639 |
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+ | 0.1837 | 10.02 | 442210 | 1.1805 | 0.7621 | 0.7624 | 0.7621 | 0.7621 |
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+ | 0.1667 | 11.02 | 486431 | 1.3017 | 0.7658 | 0.7659 | 0.7659 | 0.7658 |
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+ | 0.1531 | 12.02 | 530652 | 1.2947 | 0.7627 | 0.7628 | 0.7627 | 0.7627 |
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+ | 0.1377 | 13.02 | 574873 | 1.3877 | 0.7639 | 0.7639 | 0.7639 | 0.7639 |
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+ | 0.1249 | 14.02 | 619094 | 1.4468 | 0.7613 | 0.7616 | 0.7613 | 0.7612 |
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+ | 0.1129 | 15.02 | 663315 | 1.4951 | 0.7620 | 0.7621 | 0.7620 | 0.7620 |
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+ | 0.103 | 16.02 | 707536 | 1.5599 | 0.7619 | 0.7624 | 0.7619 | 0.7618 |
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+ | 0.0937 | 17.03 | 751757 | 1.6270 | 0.7615 | 0.7616 | 0.7615 | 0.7615 |
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+ | 0.0864 | 18.03 | 795978 | 1.6918 | 0.7622 | 0.7624 | 0.7622 | 0.7621 |
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+ | 0.0796 | 19.03 | 840199 | 1.7094 | 0.7636 | 0.7637 | 0.7636 | 0.7636 |
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+
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+
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+ ### Framework versions
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+
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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