metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: Version3ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold2
results: []
Version3ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_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: 0.7081
- Qwk: 0.5886
- Mse: 0.7076
- Rmse: 0.8412
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 | 10.7808 | -0.0004 | 10.7811 | 3.2835 |
| No log | 2.0 | 6 | 7.8207 | 0.0 | 7.8208 | 2.7966 |
| No log | 3.0 | 9 | 5.4718 | 0.0147 | 5.4722 | 2.3393 |
| No log | 4.0 | 12 | 4.0428 | 0.0039 | 4.0432 | 2.0108 |
| No log | 5.0 | 15 | 2.8634 | 0.0 | 2.8638 | 1.6923 |
| No log | 6.0 | 18 | 2.0999 | 0.0847 | 2.1003 | 1.4493 |
| No log | 7.0 | 21 | 1.5505 | 0.0107 | 1.5509 | 1.2454 |
| No log | 8.0 | 24 | 1.1710 | 0.0107 | 1.1714 | 1.0823 |
| No log | 9.0 | 27 | 0.9625 | 0.0 | 0.9630 | 0.9813 |
| No log | 10.0 | 30 | 0.8309 | 0.0430 | 0.8314 | 0.9118 |
| No log | 11.0 | 33 | 0.8321 | 0.0327 | 0.8326 | 0.9124 |
| No log | 12.0 | 36 | 1.0067 | 0.0164 | 1.0072 | 1.0036 |
| No log | 13.0 | 39 | 1.2984 | 0.1608 | 1.2988 | 1.1396 |
| No log | 14.0 | 42 | 1.2769 | 0.2402 | 1.2770 | 1.1300 |
| No log | 15.0 | 45 | 1.7979 | 0.0887 | 1.7980 | 1.3409 |
| No log | 16.0 | 48 | 0.9769 | 0.3626 | 0.9765 | 0.9882 |
| No log | 17.0 | 51 | 1.2823 | 0.3397 | 1.2814 | 1.1320 |
| No log | 18.0 | 54 | 0.8398 | 0.4649 | 0.8387 | 0.9158 |
| No log | 19.0 | 57 | 0.6987 | 0.5202 | 0.6979 | 0.8354 |
| No log | 20.0 | 60 | 0.8365 | 0.5647 | 0.8352 | 0.9139 |
| No log | 21.0 | 63 | 0.8968 | 0.4973 | 0.8966 | 0.9469 |
| No log | 22.0 | 66 | 0.8559 | 0.5703 | 0.8549 | 0.9246 |
| No log | 23.0 | 69 | 0.7903 | 0.5742 | 0.7896 | 0.8886 |
| No log | 24.0 | 72 | 0.8975 | 0.5165 | 0.8974 | 0.9473 |
| No log | 25.0 | 75 | 0.8517 | 0.5799 | 0.8510 | 0.9225 |
| No log | 26.0 | 78 | 0.7421 | 0.5633 | 0.7420 | 0.8614 |
| No log | 27.0 | 81 | 0.9198 | 0.5586 | 0.9189 | 0.9586 |
| No log | 28.0 | 84 | 0.6642 | 0.6112 | 0.6636 | 0.8146 |
| No log | 29.0 | 87 | 1.4510 | 0.4515 | 1.4495 | 1.2040 |
| No log | 30.0 | 90 | 0.8165 | 0.5778 | 0.8155 | 0.9030 |
| No log | 31.0 | 93 | 0.9218 | 0.4588 | 0.9217 | 0.9601 |
| No log | 32.0 | 96 | 0.7112 | 0.5726 | 0.7106 | 0.8430 |
| No log | 33.0 | 99 | 1.0820 | 0.5136 | 1.0804 | 1.0394 |
| No log | 34.0 | 102 | 0.9525 | 0.4967 | 0.9520 | 0.9757 |
| No log | 35.0 | 105 | 0.7906 | 0.5404 | 0.7900 | 0.8888 |
| No log | 36.0 | 108 | 1.2678 | 0.4394 | 1.2665 | 1.1254 |
| No log | 37.0 | 111 | 1.0744 | 0.4724 | 1.0735 | 1.0361 |
| No log | 38.0 | 114 | 0.8404 | 0.5616 | 0.8395 | 0.9162 |
| No log | 39.0 | 117 | 0.8493 | 0.5609 | 0.8486 | 0.9212 |
| No log | 40.0 | 120 | 0.8786 | 0.5563 | 0.8779 | 0.9370 |
| No log | 41.0 | 123 | 0.7582 | 0.5894 | 0.7574 | 0.8703 |
| No log | 42.0 | 126 | 0.6573 | 0.5947 | 0.6567 | 0.8104 |
| No log | 43.0 | 129 | 0.8428 | 0.5411 | 0.8422 | 0.9177 |
| No log | 44.0 | 132 | 1.5438 | 0.3934 | 1.5429 | 1.2421 |
| No log | 45.0 | 135 | 1.2301 | 0.4344 | 1.2294 | 1.1088 |
| No log | 46.0 | 138 | 0.7225 | 0.5964 | 0.7219 | 0.8497 |
| No log | 47.0 | 141 | 0.7421 | 0.5906 | 0.7415 | 0.8611 |
| No log | 48.0 | 144 | 0.7081 | 0.5886 | 0.7076 | 0.8412 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0