metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: '20230822120608'
results: []
20230822120608
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: 19.9899
- Accuracy: 0.5271
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 | 27.0766 | 0.5271 |
| 29.447 | 2.0 | 624 | 24.0887 | 0.4729 |
| 29.447 | 3.0 | 936 | 23.9640 | 0.5271 |
| 27.7172 | 4.0 | 1248 | 22.0260 | 0.4729 |
| 26.4345 | 5.0 | 1560 | 22.0502 | 0.4729 |
| 26.4345 | 6.0 | 1872 | 22.9337 | 0.5271 |
| 27.0832 | 7.0 | 2184 | 21.2859 | 0.5271 |
| 27.0832 | 8.0 | 2496 | 21.4709 | 0.4729 |
| 25.6523 | 9.0 | 2808 | 20.3539 | 0.5271 |
| 25.5288 | 10.0 | 3120 | 21.2982 | 0.5271 |
| 25.5288 | 11.0 | 3432 | 22.0599 | 0.5271 |
| 25.9846 | 12.0 | 3744 | 22.1000 | 0.5271 |
| 26.609 | 13.0 | 4056 | 24.1133 | 0.4729 |
| 26.609 | 14.0 | 4368 | 22.4392 | 0.4729 |
| 26.7751 | 15.0 | 4680 | 22.0514 | 0.4729 |
| 26.7751 | 16.0 | 4992 | 21.4413 | 0.5271 |
| 25.8484 | 17.0 | 5304 | 21.6759 | 0.5271 |
| 25.7937 | 18.0 | 5616 | 21.2726 | 0.5271 |
| 25.7937 | 19.0 | 5928 | 21.2489 | 0.5271 |
| 25.6479 | 20.0 | 6240 | 21.1881 | 0.5271 |
| 25.6144 | 21.0 | 6552 | 21.0354 | 0.5271 |
| 25.6144 | 22.0 | 6864 | 21.0688 | 0.4729 |
| 25.4368 | 23.0 | 7176 | 21.2154 | 0.4729 |
| 25.4368 | 24.0 | 7488 | 21.2348 | 0.4729 |
| 25.5564 | 25.0 | 7800 | 21.1510 | 0.5271 |
| 25.5495 | 26.0 | 8112 | 21.3992 | 0.5271 |
| 25.5495 | 27.0 | 8424 | 21.4035 | 0.4729 |
| 25.4536 | 28.0 | 8736 | 20.9643 | 0.5271 |
| 25.3641 | 29.0 | 9048 | 20.7780 | 0.4729 |
| 25.3641 | 30.0 | 9360 | 21.4761 | 0.5271 |
| 25.4089 | 31.0 | 9672 | 21.1053 | 0.4729 |
| 25.4089 | 32.0 | 9984 | 21.1557 | 0.5271 |
| 25.6056 | 33.0 | 10296 | 21.0180 | 0.5271 |
| 25.5078 | 34.0 | 10608 | 21.1026 | 0.4729 |
| 25.5078 | 35.0 | 10920 | 21.3723 | 0.4729 |
| 25.6607 | 36.0 | 11232 | 21.4309 | 0.4729 |
| 25.9641 | 37.0 | 11544 | 21.4083 | 0.5271 |
| 25.9641 | 38.0 | 11856 | 21.2875 | 0.5271 |
| 25.6756 | 39.0 | 12168 | 21.4538 | 0.5271 |
| 25.6756 | 40.0 | 12480 | 21.1870 | 0.4729 |
| 25.4709 | 41.0 | 12792 | 21.0796 | 0.5271 |
| 25.2913 | 42.0 | 13104 | 20.9412 | 0.5271 |
| 25.2913 | 43.0 | 13416 | 20.8932 | 0.5271 |
| 25.1541 | 44.0 | 13728 | 20.9172 | 0.4729 |
| 25.0679 | 45.0 | 14040 | 20.6787 | 0.5271 |
| 25.0679 | 46.0 | 14352 | 20.6308 | 0.4729 |
| 24.965 | 47.0 | 14664 | 20.5240 | 0.5271 |
| 24.965 | 48.0 | 14976 | 20.6378 | 0.4729 |
| 24.8969 | 49.0 | 15288 | 20.5030 | 0.4729 |
| 24.8319 | 50.0 | 15600 | 20.3257 | 0.5271 |
| 24.8319 | 51.0 | 15912 | 20.2990 | 0.5271 |
| 24.7301 | 52.0 | 16224 | 20.3661 | 0.4729 |
| 24.6644 | 53.0 | 16536 | 20.2088 | 0.5271 |
| 24.6644 | 54.0 | 16848 | 20.1543 | 0.5271 |
| 24.5917 | 55.0 | 17160 | 20.0860 | 0.4729 |
| 24.5917 | 56.0 | 17472 | 20.0672 | 0.5271 |
| 24.5505 | 57.0 | 17784 | 20.0518 | 0.5271 |
| 24.5065 | 58.0 | 18096 | 20.0036 | 0.5271 |
| 24.5065 | 59.0 | 18408 | 19.9939 | 0.5271 |
| 24.4773 | 60.0 | 18720 | 19.9899 | 0.5271 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3