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ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_fold4
genki10/ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_fold4
ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_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 13, 2025
- Updated
- Feb 13, 2025
- SHA
- c563b592
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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_AugV10_k3_task1_organization_k3_k3_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: 1.5806
- Qwk: 0.2954
- Mse: 1.5806
- Rmse: 1.2572
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 | 3 | 11.7848 | 0.0047 | 11.7848 | 3.4329 |
| No log | 2.0 | 6 | 9.7707 | 0.0018 | 9.7707 | 3.1258 |
| No log | 3.0 | 9 | 7.2379 | 0.0018 | 7.2379 | 2.6903 |
| No log | 4.0 | 12 | 6.0777 | -0.0065 | 6.0777 | 2.4653 |
| No log | 5.0 | 15 | 4.0602 | 0.0103 | 4.0602 | 2.0150 |
| No log | 6.0 | 18 | 3.1000 | 0.0040 | 3.1000 | 1.7607 |
| No log | 7.0 | 21 | 2.0926 | 0.1132 | 2.0926 | 1.4466 |
| No log | 8.0 | 24 | 2.0512 | 0.0498 | 2.0512 | 1.4322 |
| No log | 9.0 | 27 | 1.2106 | 0.0316 | 1.2106 | 1.1003 |
| No log | 10.0 | 30 | 1.5829 | 0.0878 | 1.5829 | 1.2581 |
| No log | 11.0 | 33 | 1.8399 | 0.1272 | 1.8399 | 1.3564 |
| No log | 12.0 | 36 | 1.1755 | 0.0719 | 1.1755 | 1.0842 |
| No log | 13.0 | 39 | 2.0650 | 0.1329 | 2.0650 | 1.4370 |
| No log | 14.0 | 42 | 1.3652 | 0.1317 | 1.3652 | 1.1684 |
| No log | 15.0 | 45 | 1.9195 | 0.1227 | 1.9195 | 1.3855 |
| No log | 16.0 | 48 | 1.0689 | 0.2598 | 1.0689 | 1.0339 |
| No log | 17.0 | 51 | 1.8984 | 0.1092 | 1.8984 | 1.3778 |
| No log | 18.0 | 54 | 1.4361 | 0.2454 | 1.4361 | 1.1984 |
| No log | 19.0 | 57 | 1.9733 | 0.1499 | 1.9733 | 1.4047 |
| No log | 20.0 | 60 | 1.4637 | 0.2356 | 1.4637 | 1.2099 |
| No log | 21.0 | 63 | 2.2005 | 0.0753 | 2.2005 | 1.4834 |
| No log | 22.0 | 66 | 1.6116 | 0.1751 | 1.6116 | 1.2695 |
| No log | 23.0 | 69 | 2.2553 | 0.1236 | 2.2553 | 1.5018 |
| No log | 24.0 | 72 | 2.5172 | 0.0708 | 2.5172 | 1.5866 |
| No log | 25.0 | 75 | 2.0880 | 0.1035 | 2.0880 | 1.4450 |
| No log | 26.0 | 78 | 2.8971 | 0.0655 | 2.8971 | 1.7021 |
| No log | 27.0 | 81 | 2.4190 | 0.1160 | 2.4190 | 1.5553 |
| No log | 28.0 | 84 | 2.5951 | 0.1019 | 2.5951 | 1.6109 |
| No log | 29.0 | 87 | 1.9093 | 0.1718 | 1.9093 | 1.3818 |
| No log | 30.0 | 90 | 3.7374 | 0.0492 | 3.7374 | 1.9332 |
| No log | 31.0 | 93 | 2.2339 | 0.1337 | 2.2339 | 1.4946 |
| No log | 32.0 | 96 | 1.3679 | 0.3064 | 1.3679 | 1.1696 |
| No log | 33.0 | 99 | 2.1052 | 0.1967 | 2.1052 | 1.4509 |
| No log | 34.0 | 102 | 1.5267 | 0.3243 | 1.5267 | 1.2356 |
| No log | 35.0 | 105 | 1.7447 | 0.2604 | 1.7447 | 1.3209 |
| No log | 36.0 | 108 | 2.2438 | 0.2023 | 2.2438 | 1.4979 |
| No log | 37.0 | 111 | 1.7106 | 0.2653 | 1.7106 | 1.3079 |
| No log | 38.0 | 114 | 2.1309 | 0.2006 | 2.1309 | 1.4598 |
| No log | 39.0 | 117 | 1.6206 | 0.2783 | 1.6206 | 1.2730 |
| No log | 40.0 | 120 | 2.0544 | 0.2017 | 2.0544 | 1.4333 |
| No log | 41.0 | 123 | 1.6511 | 0.2901 | 1.6511 | 1.2850 |
| No log | 42.0 | 126 | 2.1473 | 0.2085 | 2.1473 | 1.4654 |
| No log | 43.0 | 129 | 1.6338 | 0.3020 | 1.6338 | 1.2782 |
| No log | 44.0 | 132 | 1.7822 | 0.2602 | 1.7822 | 1.3350 |
| No log | 45.0 | 135 | 1.6700 | 0.2957 | 1.6700 | 1.2923 |
| No log | 46.0 | 138 | 1.8994 | 0.2337 | 1.8994 | 1.3782 |
| No log | 47.0 | 141 | 1.9166 | 0.2010 | 1.9166 | 1.3844 |
| No log | 48.0 | 144 | 1.5937 | 0.2700 | 1.5937 | 1.2624 |
| No log | 49.0 | 147 | 1.9411 | 0.1804 | 1.9411 | 1.3932 |
| No log | 50.0 | 150 | 1.6557 | 0.2565 | 1.6557 | 1.2867 |
| No log | 51.0 | 153 | 1.7849 | 0.2490 | 1.7849 | 1.3360 |
| No log | 52.0 | 156 | 1.6673 | 0.2781 | 1.6673 | 1.2912 |
| No log | 53.0 | 159 | 1.7403 | 0.2549 | 1.7403 | 1.3192 |
| No log | 54.0 | 162 | 1.5806 | 0.2954 | 1.5806 | 1.2572 |
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 13, 2025
- Updated
- Feb 13, 2025