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bert-finetuned-sem_eval-english
amitkayal/bert-finetuned-sem_eval-english
bert-finetuned-sem_eval-english is a text classification model from amitkayal. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Aug 11, 2022
- Updated
- Aug 11, 2022
- SHA
- 88b2f088
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bert-finetuned-sem_eval-english
This model is a fine-tuned version of bert-base-uncased on the sem_eval_2018_task_1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3131
- F1: 0.7114
- Roc Auc: 0.8046
- Accuracy: 0.2810
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4067 | 1.0 | 855 | 0.3205 | 0.6756 | 0.7766 | 0.2709 |
| 0.2828 | 2.0 | 1710 | 0.3062 | 0.7058 | 0.7973 | 0.3014 |
| 0.239 | 3.0 | 2565 | 0.3122 | 0.7100 | 0.8038 | 0.2810 |
| 0.2145 | 4.0 | 3420 | 0.3131 | 0.7114 | 0.8046 | 0.2810 |
| 0.1888 | 5.0 | 4275 | 0.3167 | 0.7096 | 0.8022 | 0.2844 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Aug 11, 2022
- Updated
- Aug 11, 2022