metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: '20230824164037'
results: []
20230824164037
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: 0.7104
- Accuracy: 0.7617
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: 0.005
- train_batch_size: 16
- eval_batch_size: 8
- seed: 11
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 80.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 156 | 0.8540 | 0.5307 |
No log | 2.0 | 312 | 0.6894 | 0.4838 |
No log | 3.0 | 468 | 1.2065 | 0.4729 |
1.0004 | 4.0 | 624 | 0.6386 | 0.5487 |
1.0004 | 5.0 | 780 | 0.6979 | 0.5199 |
1.0004 | 6.0 | 936 | 0.6102 | 0.6173 |
0.8189 | 7.0 | 1092 | 0.9162 | 0.5848 |
0.8189 | 8.0 | 1248 | 0.7055 | 0.6282 |
0.8189 | 9.0 | 1404 | 0.5689 | 0.7004 |
0.7207 | 10.0 | 1560 | 1.0166 | 0.6282 |
0.7207 | 11.0 | 1716 | 0.8185 | 0.4946 |
0.7207 | 12.0 | 1872 | 0.5053 | 0.7148 |
0.6822 | 13.0 | 2028 | 0.5296 | 0.7184 |
0.6822 | 14.0 | 2184 | 0.6259 | 0.7040 |
0.6822 | 15.0 | 2340 | 0.9773 | 0.6426 |
0.6822 | 16.0 | 2496 | 0.7401 | 0.6462 |
0.6238 | 17.0 | 2652 | 0.4929 | 0.7148 |
0.6238 | 18.0 | 2808 | 0.5547 | 0.7256 |
0.6238 | 19.0 | 2964 | 0.5692 | 0.7220 |
0.5327 | 20.0 | 3120 | 0.9119 | 0.6498 |
0.5327 | 21.0 | 3276 | 0.6083 | 0.7004 |
0.5327 | 22.0 | 3432 | 0.5836 | 0.7112 |
0.4818 | 23.0 | 3588 | 0.5820 | 0.7292 |
0.4818 | 24.0 | 3744 | 0.5506 | 0.7292 |
0.4818 | 25.0 | 3900 | 0.6027 | 0.7256 |
0.4199 | 26.0 | 4056 | 0.5265 | 0.7437 |
0.4199 | 27.0 | 4212 | 0.6094 | 0.7076 |
0.4199 | 28.0 | 4368 | 0.6170 | 0.7220 |
0.4001 | 29.0 | 4524 | 0.5932 | 0.7329 |
0.4001 | 30.0 | 4680 | 0.6954 | 0.7220 |
0.4001 | 31.0 | 4836 | 0.6963 | 0.7437 |
0.4001 | 32.0 | 4992 | 0.6431 | 0.7545 |
0.3272 | 33.0 | 5148 | 0.9597 | 0.7040 |
0.3272 | 34.0 | 5304 | 0.6982 | 0.7365 |
0.3272 | 35.0 | 5460 | 0.6270 | 0.7437 |
0.2947 | 36.0 | 5616 | 1.0674 | 0.7004 |
0.2947 | 37.0 | 5772 | 0.8835 | 0.7256 |
0.2947 | 38.0 | 5928 | 0.9769 | 0.6859 |
0.266 | 39.0 | 6084 | 0.6855 | 0.7581 |
0.266 | 40.0 | 6240 | 0.7246 | 0.7509 |
0.266 | 41.0 | 6396 | 0.6901 | 0.7690 |
0.2254 | 42.0 | 6552 | 0.7170 | 0.7509 |
0.2254 | 43.0 | 6708 | 0.7532 | 0.7473 |
0.2254 | 44.0 | 6864 | 0.7347 | 0.7617 |
0.2188 | 45.0 | 7020 | 0.6478 | 0.7509 |
0.2188 | 46.0 | 7176 | 0.7903 | 0.7545 |
0.2188 | 47.0 | 7332 | 0.9367 | 0.7220 |
0.2188 | 48.0 | 7488 | 0.8417 | 0.7690 |
0.2166 | 49.0 | 7644 | 0.8226 | 0.7617 |
0.2166 | 50.0 | 7800 | 0.6278 | 0.7545 |
0.2166 | 51.0 | 7956 | 0.7471 | 0.7473 |
0.1828 | 52.0 | 8112 | 0.7728 | 0.7617 |
0.1828 | 53.0 | 8268 | 0.7733 | 0.7690 |
0.1828 | 54.0 | 8424 | 0.7554 | 0.7581 |
0.163 | 55.0 | 8580 | 0.8025 | 0.7653 |
0.163 | 56.0 | 8736 | 0.8769 | 0.7617 |
0.163 | 57.0 | 8892 | 0.6569 | 0.7473 |
0.1563 | 58.0 | 9048 | 0.7166 | 0.7653 |
0.1563 | 59.0 | 9204 | 0.8688 | 0.7617 |
0.1563 | 60.0 | 9360 | 0.7254 | 0.7617 |
0.1423 | 61.0 | 9516 | 0.8286 | 0.7545 |
0.1423 | 62.0 | 9672 | 0.7656 | 0.7545 |
0.1423 | 63.0 | 9828 | 0.8362 | 0.7617 |
0.1423 | 64.0 | 9984 | 0.7287 | 0.7617 |
0.1355 | 65.0 | 10140 | 0.8451 | 0.7581 |
0.1355 | 66.0 | 10296 | 0.6854 | 0.7617 |
0.1355 | 67.0 | 10452 | 0.7272 | 0.7581 |
0.1321 | 68.0 | 10608 | 0.6530 | 0.7617 |
0.1321 | 69.0 | 10764 | 0.8535 | 0.7653 |
0.1321 | 70.0 | 10920 | 0.7803 | 0.7653 |
0.1217 | 71.0 | 11076 | 0.7409 | 0.7617 |
0.1217 | 72.0 | 11232 | 0.7044 | 0.7617 |
0.1217 | 73.0 | 11388 | 0.6501 | 0.7653 |
0.1224 | 74.0 | 11544 | 0.7102 | 0.7617 |
0.1224 | 75.0 | 11700 | 0.7050 | 0.7617 |
0.1224 | 76.0 | 11856 | 0.7103 | 0.7617 |
0.1173 | 77.0 | 12012 | 0.6821 | 0.7617 |
0.1173 | 78.0 | 12168 | 0.7196 | 0.7617 |
0.1173 | 79.0 | 12324 | 0.7048 | 0.7617 |
0.1173 | 80.0 | 12480 | 0.7104 | 0.7617 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3