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ASAP_FineTuningBERT_AugV8_k1_task1_organization_fold1
genki10/ASAP_FineTuningBERT_AugV8_k1_task1_organization_fold1
ASAP_FineTuningBERT_AugV8_k1_task1_organization_fold1 is a text classification model from genki10. 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 3, 2025
- Updated
- Feb 4, 2025
- SHA
- 67a15a83
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Base models
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. -->
ASAP_FineTuningBERT_AugV8_k1_task1_organization_fold1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2591
- Qwk: 0.0759
- Mse: 2.2627
- Rmse: 1.5042
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 1.0 | 5 | 5.1112 | 0.0 | 5.1173 | 2.2621 |
| 5.2467 | 2.0 | 10 | 3.0480 | 0.0 | 3.0524 | 1.7471 |
| 5.2467 | 3.0 | 15 | 2.2591 | 0.0759 | 2.2627 | 1.5042 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 3, 2025
- Updated
- Feb 4, 2025