metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: 1e-2_10_0.1
results: []
1e-2_10_0.1
This model is a fine-tuned version of bert-large-cased on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6265
- Accuracy: 0.5126
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: 0.01
- train_batch_size: 8
- eval_batch_size: 8
- seed: 11
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 312 | 0.6257 | 0.5307 |
| 1.3002 | 2.0 | 624 | 1.0407 | 0.5271 |
| 1.3002 | 3.0 | 936 | 1.4050 | 0.5271 |
| 1.0663 | 4.0 | 1248 | 0.9796 | 0.5271 |
| 1.0554 | 5.0 | 1560 | 1.4166 | 0.5271 |
| 1.0554 | 6.0 | 1872 | 0.9151 | 0.5271 |
| 0.8523 | 7.0 | 2184 | 0.8469 | 0.5271 |
| 0.8523 | 8.0 | 2496 | 0.8390 | 0.5271 |
| 0.8445 | 9.0 | 2808 | 0.7439 | 0.4729 |
| 0.8722 | 10.0 | 3120 | 0.6458 | 0.5343 |
| 0.8722 | 11.0 | 3432 | 0.7906 | 0.4729 |
| 0.8432 | 12.0 | 3744 | 0.6429 | 0.4946 |
| 0.7932 | 13.0 | 4056 | 0.6503 | 0.5307 |
| 0.7932 | 14.0 | 4368 | 0.7167 | 0.5271 |
| 0.7687 | 15.0 | 4680 | 0.6584 | 0.4765 |
| 0.7687 | 16.0 | 4992 | 0.6324 | 0.4874 |
| 0.7569 | 17.0 | 5304 | 0.7912 | 0.5271 |
| 0.7369 | 18.0 | 5616 | 0.7309 | 0.4729 |
| 0.7369 | 19.0 | 5928 | 0.6402 | 0.5126 |
| 0.7632 | 20.0 | 6240 | 0.7055 | 0.5271 |
| 0.7321 | 21.0 | 6552 | 0.6247 | 0.5271 |
| 0.7321 | 22.0 | 6864 | 0.7055 | 0.5271 |
| 0.7151 | 23.0 | 7176 | 0.6276 | 0.5343 |
| 0.7151 | 24.0 | 7488 | 0.6245 | 0.5271 |
| 0.7092 | 25.0 | 7800 | 0.6266 | 0.5126 |
| 0.7311 | 26.0 | 8112 | 0.6983 | 0.5271 |
| 0.7311 | 27.0 | 8424 | 0.6762 | 0.4729 |
| 0.7027 | 28.0 | 8736 | 0.6316 | 0.5018 |
| 0.7007 | 29.0 | 9048 | 0.6505 | 0.4729 |
| 0.7007 | 30.0 | 9360 | 0.7682 | 0.5271 |
| 0.6974 | 31.0 | 9672 | 0.6616 | 0.5271 |
| 0.6974 | 32.0 | 9984 | 0.6322 | 0.5271 |
| 0.6974 | 33.0 | 10296 | 0.6302 | 0.5271 |
| 0.6786 | 34.0 | 10608 | 0.6764 | 0.4729 |
| 0.6786 | 35.0 | 10920 | 0.6569 | 0.4729 |
| 0.692 | 36.0 | 11232 | 0.6584 | 0.4729 |
| 0.6814 | 37.0 | 11544 | 0.6636 | 0.5271 |
| 0.6814 | 38.0 | 11856 | 0.6477 | 0.4729 |
| 0.6767 | 39.0 | 12168 | 0.6294 | 0.5271 |
| 0.6767 | 40.0 | 12480 | 0.6487 | 0.4585 |
| 0.6762 | 41.0 | 12792 | 0.6301 | 0.5307 |
| 0.6682 | 42.0 | 13104 | 0.6252 | 0.5271 |
| 0.6682 | 43.0 | 13416 | 0.6249 | 0.5271 |
| 0.6738 | 44.0 | 13728 | 0.6334 | 0.5271 |
| 0.667 | 45.0 | 14040 | 0.6248 | 0.5271 |
| 0.667 | 46.0 | 14352 | 0.6390 | 0.5090 |
| 0.6633 | 47.0 | 14664 | 0.6622 | 0.4729 |
| 0.6633 | 48.0 | 14976 | 0.6267 | 0.4874 |
| 0.6573 | 49.0 | 15288 | 0.6256 | 0.5271 |
| 0.6559 | 50.0 | 15600 | 0.6306 | 0.4838 |
| 0.6559 | 51.0 | 15912 | 0.6412 | 0.4729 |
| 0.6455 | 52.0 | 16224 | 0.6634 | 0.4729 |
| 0.6484 | 53.0 | 16536 | 0.6247 | 0.5271 |
| 0.6484 | 54.0 | 16848 | 0.6267 | 0.5271 |
| 0.6417 | 55.0 | 17160 | 0.6295 | 0.4838 |
| 0.6417 | 56.0 | 17472 | 0.6256 | 0.5271 |
| 0.6395 | 57.0 | 17784 | 0.6268 | 0.4946 |
| 0.6418 | 58.0 | 18096 | 0.6267 | 0.4838 |
| 0.6418 | 59.0 | 18408 | 0.6260 | 0.5271 |
| 0.6373 | 60.0 | 18720 | 0.6265 | 0.5126 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3