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bert-base-uncased-imdb
fabriceyhc/bert-base-uncased-imdb
bert-base-uncased-imdb is a text classification model from fabriceyhc. 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
- Mar 2, 2022
- Updated
- Aug 30, 2022
- SHA
- 666b83f6
Try a prompt
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-uncased-imdb
This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.4942
- Accuracy: 0.9126
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1546
- training_steps: 15468
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3952 | 0.65 | 2000 | 0.4012 | 0.86 |
| 0.2954 | 1.29 | 4000 | 0.4535 | 0.892 |
| 0.2595 | 1.94 | 6000 | 0.4320 | 0.892 |
| 0.1516 | 2.59 | 8000 | 0.5309 | 0.896 |
| 0.1167 | 3.23 | 10000 | 0.4070 | 0.928 |
| 0.0624 | 3.88 | 12000 | 0.5055 | 0.908 |
| 0.0329 | 4.52 | 14000 | 0.4342 | 0.92 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.6.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Aug 30, 2022