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bert-base-finetuned-ynat
zgotter/bert-base-finetuned-ynat
bert-base-finetuned-ynat is a text classification model from zgotter. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Sep 24, 2021
- SHA
- ef7436ca
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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-base-finetuned-ynat
This model is a fine-tuned version of klue/bert-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3710
- F1: 0.8669
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: 256
- eval_batch_size: 256
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 179 | 0.4223 | 0.8549 |
| No log | 2.0 | 358 | 0.3710 | 0.8669 |
| 0.2576 | 3.0 | 537 | 0.3891 | 0.8631 |
| 0.2576 | 4.0 | 716 | 0.3968 | 0.8612 |
| 0.2576 | 5.0 | 895 | 0.4044 | 0.8617 |
Framework versions
- Transformers 4.10.3
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- Sep 24, 2021