20230822173808
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: 0.3493
- Accuracy: 0.6968
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: 0.004
- 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 | 0.3774 | 0.5162 |
| 0.5343 | 2.0 | 624 | 0.3506 | 0.5018 |
| 0.5343 | 3.0 | 936 | 0.4575 | 0.4729 |
| 0.4659 | 4.0 | 1248 | 0.3759 | 0.5307 |
| 0.4691 | 5.0 | 1560 | 0.3500 | 0.5812 |
| 0.4691 | 6.0 | 1872 | 0.3457 | 0.5993 |
| 0.4442 | 7.0 | 2184 | 0.3500 | 0.6101 |
| 0.4442 | 8.0 | 2496 | 0.3403 | 0.6173 |
| 0.4366 | 9.0 | 2808 | 0.3840 | 0.5776 |
| 0.4097 | 10.0 | 3120 | 0.4391 | 0.5487 |
| 0.4097 | 11.0 | 3432 | 0.3584 | 0.6029 |
| 0.3922 | 12.0 | 3744 | 0.3356 | 0.6498 |
| 0.3564 | 13.0 | 4056 | 0.3275 | 0.6931 |
| 0.3564 | 14.0 | 4368 | 0.3283 | 0.7076 |
| 0.3343 | 15.0 | 4680 | 0.3377 | 0.6462 |
| 0.3343 | 16.0 | 4992 | 0.3550 | 0.6390 |
| 0.335 | 17.0 | 5304 | 0.3370 | 0.6895 |
| 0.3233 | 18.0 | 5616 | 0.3256 | 0.6787 |
| 0.3233 | 19.0 | 5928 | 0.3174 | 0.7112 |
| 0.3232 | 20.0 | 6240 | 0.3440 | 0.6643 |
| 0.3102 | 21.0 | 6552 | 0.3375 | 0.6895 |
| 0.3102 | 22.0 | 6864 | 0.3433 | 0.6787 |
| 0.3064 | 23.0 | 7176 | 0.3690 | 0.6715 |
| 0.3064 | 24.0 | 7488 | 0.3394 | 0.6931 |
| 0.3004 | 25.0 | 7800 | 0.3377 | 0.7256 |
| 0.2962 | 26.0 | 8112 | 0.3435 | 0.6751 |
| 0.2962 | 27.0 | 8424 | 0.3182 | 0.7329 |
| 0.2937 | 28.0 | 8736 | 0.3306 | 0.7112 |
| 0.2905 | 29.0 | 9048 | 0.3362 | 0.7148 |
| 0.2905 | 30.0 | 9360 | 0.3675 | 0.6751 |
| 0.2865 | 31.0 | 9672 | 0.3406 | 0.7076 |
| 0.2865 | 32.0 | 9984 | 0.3343 | 0.7040 |
| 0.2812 | 33.0 | 10296 | 0.3472 | 0.6859 |
| 0.2727 | 34.0 | 10608 | 0.3372 | 0.7292 |
| 0.2727 | 35.0 | 10920 | 0.3575 | 0.7076 |
| 0.2735 | 36.0 | 11232 | 0.3300 | 0.7076 |
| 0.2701 | 37.0 | 11544 | 0.3585 | 0.6968 |
| 0.2701 | 38.0 | 11856 | 0.3422 | 0.7148 |
| 0.2688 | 39.0 | 12168 | 0.3579 | 0.6931 |
| 0.2688 | 40.0 | 12480 | 0.3326 | 0.7148 |
| 0.2644 | 41.0 | 12792 | 0.3464 | 0.7256 |
| 0.2637 | 42.0 | 13104 | 0.3579 | 0.6931 |
| 0.2637 | 43.0 | 13416 | 0.3489 | 0.7040 |
| 0.26 | 44.0 | 13728 | 0.3439 | 0.7076 |
| 0.2582 | 45.0 | 14040 | 0.3585 | 0.7004 |
| 0.2582 | 46.0 | 14352 | 0.3535 | 0.7076 |
| 0.2533 | 47.0 | 14664 | 0.3440 | 0.7148 |
| 0.2533 | 48.0 | 14976 | 0.3506 | 0.7040 |
| 0.2535 | 49.0 | 15288 | 0.3519 | 0.7040 |
| 0.2498 | 50.0 | 15600 | 0.3457 | 0.6931 |
| 0.2498 | 51.0 | 15912 | 0.3494 | 0.7112 |
| 0.2504 | 52.0 | 16224 | 0.3431 | 0.7040 |
| 0.2499 | 53.0 | 16536 | 0.3450 | 0.7040 |
| 0.2499 | 54.0 | 16848 | 0.3485 | 0.6895 |
| 0.2488 | 55.0 | 17160 | 0.3437 | 0.7004 |
| 0.2488 | 56.0 | 17472 | 0.3465 | 0.7004 |
| 0.2479 | 57.0 | 17784 | 0.3479 | 0.6895 |
| 0.247 | 58.0 | 18096 | 0.3447 | 0.7004 |
| 0.247 | 59.0 | 18408 | 0.3521 | 0.7004 |
| 0.2468 | 60.0 | 18720 | 0.3493 | 0.6968 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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