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bert-base-uncased-finetuned-effectiveness-redditCMV
jakub014/bert-base-uncased-finetuned-effectiveness-redditCMV
bert-base-uncased-finetuned-effectiveness-redditCMV is a text classification model from jakub014. 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
- Feb 1, 2023
- Updated
- Feb 8, 2023
- SHA
- 6eb3e5ac
Try a prompt
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-finetuned-effectiveness-redditCMV
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6920
- Accuracy: 0.6376
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|---|---|---|---|---|
| 0.6873 | 1.0 | 516 | 0.6706 | 0.5769 |
| 0.6256 | 2.0 | 1032 | 0.6424 | 0.6366 |
| 0.5197 | 3.0 | 1548 | 0.6920 | 0.6376 |
| 0.3814 | 4.0 | 2064 | 0.8641 | 0.6361 |
| 0.2589 | 5.0 | 2580 | 1.0249 | 0.6249 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 1, 2023
- Updated
- Feb 8, 2023