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ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold3
genki10/ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold3
ASAP_FineTuningBERT_AugV8_k2_task1_organization_fold3 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 3, 2025
- SHA
- 80c5ab0c
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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_k2_task1_organization_fold3
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: 1.2006
- Qwk: 0.2952
- Mse: 1.2003
- Rmse: 1.0956
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 | 2 | 9.7213 | 0.0018 | 9.7204 | 3.1178 |
| No log | 2.0 | 4 | 6.5594 | 0.0 | 6.5590 | 2.5610 |
| No log | 3.0 | 6 | 4.7546 | 0.0076 | 4.7545 | 2.1805 |
| No log | 4.0 | 8 | 3.7279 | 0.0 | 3.7279 | 1.9308 |
| 5.5568 | 5.0 | 10 | 3.0304 | 0.0 | 3.0306 | 1.7408 |
| 5.5568 | 6.0 | 12 | 2.3843 | 0.1141 | 2.3847 | 1.5443 |
| 5.5568 | 7.0 | 14 | 2.0508 | 0.0283 | 2.0512 | 1.4322 |
| 5.5568 | 8.0 | 16 | 1.5329 | 0.0202 | 1.5336 | 1.2384 |
| 5.5568 | 9.0 | 18 | 1.2167 | 0.0202 | 1.2175 | 1.1034 |
| 2.1277 | 10.0 | 20 | 1.2072 | 0.0983 | 1.2077 | 1.0989 |
| 2.1277 | 11.0 | 22 | 1.3225 | 0.1595 | 1.3228 | 1.1501 |
| 2.1277 | 12.0 | 24 | 1.1398 | 0.1653 | 1.1401 | 1.0678 |
| 2.1277 | 13.0 | 26 | 0.9363 | 0.1656 | 0.9367 | 0.9678 |
| 2.1277 | 14.0 | 28 | 0.9429 | 0.1890 | 0.9432 | 0.9712 |
| 1.7936 | 15.0 | 30 | 1.2804 | 0.1936 | 1.2806 | 1.1316 |
| 1.7936 | 16.0 | 32 | 1.3944 | 0.2227 | 1.3944 | 1.1809 |
| 1.7936 | 17.0 | 34 | 1.2971 | 0.3513 | 1.2970 | 1.1389 |
| 1.7936 | 18.0 | 36 | 1.0590 | 0.4595 | 1.0590 | 1.0291 |
| 1.7936 | 19.0 | 38 | 1.1365 | 0.3514 | 1.1364 | 1.0660 |
| 1.4754 | 20.0 | 40 | 0.8608 | 0.4748 | 0.8607 | 0.9278 |
| 1.4754 | 21.0 | 42 | 0.8912 | 0.4264 | 0.8912 | 0.9440 |
| 1.4754 | 22.0 | 44 | 0.8548 | 0.4488 | 0.8547 | 0.9245 |
| 1.4754 | 23.0 | 46 | 0.7108 | 0.5211 | 0.7107 | 0.8430 |
| 1.4754 | 24.0 | 48 | 0.9096 | 0.4145 | 0.9095 | 0.9537 |
| 0.8721 | 25.0 | 50 | 0.8851 | 0.3928 | 0.8850 | 0.9407 |
| 0.8721 | 26.0 | 52 | 0.7125 | 0.5070 | 0.7124 | 0.8440 |
| 0.8721 | 27.0 | 54 | 1.1005 | 0.2778 | 1.1005 | 1.0490 |
| 0.8721 | 28.0 | 56 | 1.0705 | 0.2818 | 1.0704 | 1.0346 |
| 0.8721 | 29.0 | 58 | 0.7957 | 0.4641 | 0.7955 | 0.8919 |
| 0.5043 | 30.0 | 60 | 1.0409 | 0.3147 | 1.0408 | 1.0202 |
| 0.5043 | 31.0 | 62 | 0.9785 | 0.3532 | 0.9783 | 0.9891 |
| 0.5043 | 32.0 | 64 | 0.8540 | 0.4761 | 0.8535 | 0.9239 |
| 0.5043 | 33.0 | 66 | 1.2006 | 0.2952 | 1.2003 | 1.0956 |
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 3, 2025