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ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold4
genki10/ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold4
ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_fold4 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 5, 2025
- Updated
- Feb 5, 2025
- SHA
- a8909591
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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_k7_task1_organization_k7_fold4
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: 1.8076
- Qwk: 0.2287
- Mse: 1.8076
- Rmse: 1.3445
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: 64
- eval_batch_size: 64
- 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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 1.0 | 6 | 7.3068 | 0.0018 | 7.3068 | 2.7031 |
| No log | 2.0 | 12 | 3.6797 | 0.0180 | 3.6797 | 1.9183 |
| No log | 3.0 | 18 | 2.4207 | 0.0148 | 2.4207 | 1.5559 |
| No log | 4.0 | 24 | 1.3920 | 0.0420 | 1.3920 | 1.1798 |
| No log | 5.0 | 30 | 1.6656 | 0.0585 | 1.6656 | 1.2906 |
| No log | 6.0 | 36 | 1.1043 | 0.0316 | 1.1043 | 1.0509 |
| No log | 7.0 | 42 | 1.3495 | 0.0710 | 1.3495 | 1.1617 |
| No log | 8.0 | 48 | 1.1888 | 0.1130 | 1.1888 | 1.0903 |
| No log | 9.0 | 54 | 1.0737 | 0.2885 | 1.0737 | 1.0362 |
| No log | 10.0 | 60 | 0.9037 | 0.3899 | 0.9037 | 0.9506 |
| No log | 11.0 | 66 | 1.8471 | 0.1888 | 1.8471 | 1.3591 |
| No log | 12.0 | 72 | 2.6621 | 0.1092 | 2.6621 | 1.6316 |
| No log | 13.0 | 78 | 1.3250 | 0.2563 | 1.3250 | 1.1511 |
| No log | 14.0 | 84 | 1.3450 | 0.2845 | 1.3450 | 1.1597 |
| No log | 15.0 | 90 | 1.3562 | 0.2478 | 1.3562 | 1.1646 |
| No log | 16.0 | 96 | 1.7269 | 0.2043 | 1.7269 | 1.3141 |
| No log | 17.0 | 102 | 1.4961 | 0.2686 | 1.4961 | 1.2232 |
| No log | 18.0 | 108 | 1.5002 | 0.2446 | 1.5002 | 1.2248 |
| No log | 19.0 | 114 | 1.2252 | 0.2839 | 1.2252 | 1.1069 |
| No log | 20.0 | 120 | 1.8076 | 0.2287 | 1.8076 | 1.3445 |
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 5, 2025
- Updated
- Feb 5, 2025