metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3
results: []
ASAP_FineTuningBERT_AugV5_k1_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: 0.5472
- Qwk: 0.6157
- Mse: 0.5468
- Rmse: 0.7395
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 2.0 | 2 | 10.1792 | 0.0 | 10.1785 | 3.1904 |
| No log | 4.0 | 4 | 8.5089 | 0.0 | 8.5083 | 2.9169 |
| No log | 6.0 | 6 | 6.9593 | 0.0 | 6.9588 | 2.6380 |
| No log | 8.0 | 8 | 5.4856 | 0.0235 | 5.4854 | 2.3421 |
| 8.9084 | 10.0 | 10 | 4.5301 | 0.0076 | 4.5301 | 2.1284 |
| 8.9084 | 12.0 | 12 | 3.7061 | 0.0 | 3.7062 | 1.9252 |
| 8.9084 | 14.0 | 14 | 3.0780 | 0.0 | 3.0783 | 1.7545 |
| 8.9084 | 16.0 | 16 | 2.4917 | 0.0806 | 2.4921 | 1.5786 |
| 8.9084 | 18.0 | 18 | 2.0632 | 0.0462 | 2.0637 | 1.4365 |
| 4.248 | 20.0 | 20 | 1.7062 | 0.0365 | 1.7068 | 1.3064 |
| 4.248 | 22.0 | 22 | 1.4205 | 0.0266 | 1.4211 | 1.1921 |
| 4.248 | 24.0 | 24 | 1.2230 | 0.0365 | 1.2236 | 1.1062 |
| 4.248 | 26.0 | 26 | 1.0188 | 0.0266 | 1.0194 | 1.0097 |
| 4.248 | 28.0 | 28 | 0.9326 | 0.1345 | 0.9331 | 0.9660 |
| 2.2317 | 30.0 | 30 | 0.7686 | 0.4194 | 0.7691 | 0.8770 |
| 2.2317 | 32.0 | 32 | 0.6643 | 0.4239 | 0.6649 | 0.8154 |
| 2.2317 | 34.0 | 34 | 0.6961 | 0.4841 | 0.6964 | 0.8345 |
| 2.2317 | 36.0 | 36 | 0.5712 | 0.4966 | 0.5715 | 0.7560 |
| 2.2317 | 38.0 | 38 | 0.5742 | 0.4828 | 0.5746 | 0.7580 |
| 1.1982 | 40.0 | 40 | 0.6294 | 0.5328 | 0.6296 | 0.7935 |
| 1.1982 | 42.0 | 42 | 0.5522 | 0.5493 | 0.5524 | 0.7432 |
| 1.1982 | 44.0 | 44 | 0.5565 | 0.5326 | 0.5567 | 0.7461 |
| 1.1982 | 46.0 | 46 | 0.5330 | 0.6138 | 0.5330 | 0.7300 |
| 1.1982 | 48.0 | 48 | 0.5267 | 0.6243 | 0.5266 | 0.7257 |
| 0.6088 | 50.0 | 50 | 0.5512 | 0.6109 | 0.5512 | 0.7424 |
| 0.6088 | 52.0 | 52 | 0.5308 | 0.6299 | 0.5307 | 0.7285 |
| 0.6088 | 54.0 | 54 | 0.5550 | 0.6454 | 0.5548 | 0.7449 |
| 0.6088 | 56.0 | 56 | 0.5786 | 0.6130 | 0.5783 | 0.7605 |
| 0.6088 | 58.0 | 58 | 0.5721 | 0.6516 | 0.5719 | 0.7562 |
| 0.3243 | 60.0 | 60 | 0.5806 | 0.6334 | 0.5804 | 0.7618 |
| 0.3243 | 62.0 | 62 | 0.5647 | 0.6108 | 0.5644 | 0.7513 |
| 0.3243 | 64.0 | 64 | 0.5766 | 0.6371 | 0.5762 | 0.7591 |
| 0.3243 | 66.0 | 66 | 0.6710 | 0.6038 | 0.6707 | 0.8190 |
| 0.3243 | 68.0 | 68 | 0.6148 | 0.6469 | 0.6144 | 0.7838 |
| 0.2165 | 70.0 | 70 | 0.6383 | 0.6439 | 0.6378 | 0.7986 |
| 0.2165 | 72.0 | 72 | 0.6265 | 0.6445 | 0.6259 | 0.7912 |
| 0.2165 | 74.0 | 74 | 0.5973 | 0.6427 | 0.5968 | 0.7725 |
| 0.2165 | 76.0 | 76 | 0.5642 | 0.6337 | 0.5638 | 0.7509 |
| 0.2165 | 78.0 | 78 | 0.6005 | 0.6137 | 0.6001 | 0.7747 |
| 0.1667 | 80.0 | 80 | 0.5892 | 0.6100 | 0.5889 | 0.7674 |
| 0.1667 | 82.0 | 82 | 0.5564 | 0.6097 | 0.5561 | 0.7457 |
| 0.1667 | 84.0 | 84 | 0.5499 | 0.6275 | 0.5496 | 0.7413 |
| 0.1667 | 86.0 | 86 | 0.5634 | 0.6148 | 0.5630 | 0.7503 |
| 0.1667 | 88.0 | 88 | 0.5774 | 0.6205 | 0.5770 | 0.7596 |
| 0.1285 | 90.0 | 90 | 0.5857 | 0.6113 | 0.5852 | 0.7650 |
| 0.1285 | 92.0 | 92 | 0.5637 | 0.6233 | 0.5633 | 0.7505 |
| 0.1285 | 94.0 | 94 | 0.5507 | 0.6195 | 0.5502 | 0.7418 |
| 0.1285 | 96.0 | 96 | 0.5484 | 0.6197 | 0.5480 | 0.7403 |
| 0.1285 | 98.0 | 98 | 0.5466 | 0.6224 | 0.5462 | 0.7390 |
| 0.0925 | 100.0 | 100 | 0.5472 | 0.6157 | 0.5468 | 0.7395 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1