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ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold2
genki10/ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold2
ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold2 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
- 2d2c6796
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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_k10_task1_organization_fold2
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: 1.6175
- Qwk: 0.1074
- Mse: 1.6174
- Rmse: 1.2718
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 | 0.25 | 2 | 11.3088 | 0.0163 | 11.3084 | 3.3628 |
| No log | 0.5 | 4 | 9.9736 | 0.0 | 9.9730 | 3.1580 |
| No log | 0.75 | 6 | 8.3499 | 0.0 | 8.3494 | 2.8895 |
| No log | 1.0 | 8 | 6.5420 | 0.0 | 6.5417 | 2.5577 |
| 6.7186 | 1.25 | 10 | 5.1128 | 0.0269 | 5.1125 | 2.2611 |
| 6.7186 | 1.5 | 12 | 3.7661 | 0.0 | 3.7660 | 1.9406 |
| 6.7186 | 1.75 | 14 | 2.6824 | 0.0 | 2.6823 | 1.6378 |
| 6.7186 | 2.0 | 16 | 2.1219 | 0.1108 | 2.1220 | 1.4567 |
| 6.7186 | 2.25 | 18 | 1.5288 | 0.0487 | 1.5289 | 1.2365 |
| 2.4051 | 2.5 | 20 | 1.2108 | 0.0318 | 1.2110 | 1.1005 |
| 2.4051 | 2.75 | 22 | 1.0970 | 0.0107 | 1.0972 | 1.0475 |
| 2.4051 | 3.0 | 24 | 1.1616 | 0.0 | 1.1619 | 1.0779 |
| 2.4051 | 3.25 | 26 | 1.2406 | 0.0 | 1.2409 | 1.1139 |
| 2.4051 | 3.5 | 28 | 1.4391 | 0.0 | 1.4393 | 1.1997 |
| 1.8699 | 3.75 | 30 | 1.3248 | 0.0 | 1.3250 | 1.1511 |
| 1.8699 | 4.0 | 32 | 1.2762 | 0.0345 | 1.2763 | 1.1297 |
| 1.8699 | 4.25 | 34 | 1.3223 | 0.0577 | 1.3223 | 1.1499 |
| 1.8699 | 4.5 | 36 | 1.6175 | 0.1074 | 1.6174 | 1.2718 |
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