|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- super_glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: 1_8e-3_1_0.1 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# 1_8e-3_1_0.1 |
|
|
|
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9505 |
|
- Accuracy: 0.7318 |
|
|
|
## 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: 0.008 |
|
- 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: 100.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 1.3959 | 1.0 | 590 | 0.9510 | 0.3786 | |
|
| 1.0927 | 2.0 | 1180 | 0.6855 | 0.4780 | |
|
| 0.9921 | 3.0 | 1770 | 1.4020 | 0.3783 | |
|
| 1.039 | 4.0 | 2360 | 0.9930 | 0.3835 | |
|
| 0.877 | 5.0 | 2950 | 1.3595 | 0.6217 | |
|
| 0.8304 | 6.0 | 3540 | 0.6007 | 0.6648 | |
|
| 0.7152 | 7.0 | 4130 | 1.3841 | 0.4086 | |
|
| 0.7225 | 8.0 | 4720 | 0.7135 | 0.6183 | |
|
| 0.6522 | 9.0 | 5310 | 0.5864 | 0.6966 | |
|
| 0.6306 | 10.0 | 5900 | 1.1053 | 0.6318 | |
|
| 0.6533 | 11.0 | 6490 | 0.6681 | 0.6939 | |
|
| 0.5693 | 12.0 | 7080 | 0.6281 | 0.6777 | |
|
| 0.569 | 13.0 | 7670 | 0.6301 | 0.6523 | |
|
| 0.5168 | 14.0 | 8260 | 0.6110 | 0.6878 | |
|
| 0.5071 | 15.0 | 8850 | 0.6350 | 0.7083 | |
|
| 0.5042 | 16.0 | 9440 | 0.6348 | 0.7183 | |
|
| 0.4678 | 17.0 | 10030 | 1.0429 | 0.6067 | |
|
| 0.4545 | 18.0 | 10620 | 0.7921 | 0.6780 | |
|
| 0.4216 | 19.0 | 11210 | 0.6437 | 0.7245 | |
|
| 0.3986 | 20.0 | 11800 | 0.7142 | 0.7159 | |
|
| 0.3871 | 21.0 | 12390 | 0.6949 | 0.7131 | |
|
| 0.3852 | 22.0 | 12980 | 0.6870 | 0.7235 | |
|
| 0.3519 | 23.0 | 13570 | 0.7979 | 0.7 | |
|
| 0.3271 | 24.0 | 14160 | 0.9015 | 0.6875 | |
|
| 0.3136 | 25.0 | 14750 | 0.8513 | 0.7092 | |
|
| 0.278 | 26.0 | 15340 | 0.8899 | 0.6869 | |
|
| 0.2931 | 27.0 | 15930 | 0.7898 | 0.7150 | |
|
| 0.2712 | 28.0 | 16520 | 0.8953 | 0.7294 | |
|
| 0.2494 | 29.0 | 17110 | 0.8243 | 0.7217 | |
|
| 0.2568 | 30.0 | 17700 | 0.8979 | 0.7156 | |
|
| 0.2488 | 31.0 | 18290 | 1.0504 | 0.7211 | |
|
| 0.2568 | 32.0 | 18880 | 0.8953 | 0.7107 | |
|
| 0.2465 | 33.0 | 19470 | 0.8415 | 0.7208 | |
|
| 0.2077 | 34.0 | 20060 | 1.0351 | 0.7083 | |
|
| 0.2202 | 35.0 | 20650 | 0.9620 | 0.7202 | |
|
| 0.2224 | 36.0 | 21240 | 0.8594 | 0.7251 | |
|
| 0.2133 | 37.0 | 21830 | 0.9035 | 0.7257 | |
|
| 0.1881 | 38.0 | 22420 | 0.9327 | 0.7153 | |
|
| 0.201 | 39.0 | 23010 | 0.9521 | 0.7220 | |
|
| 0.197 | 40.0 | 23600 | 0.9997 | 0.7199 | |
|
| 0.1949 | 41.0 | 24190 | 1.0048 | 0.7355 | |
|
| 0.1739 | 42.0 | 24780 | 0.9031 | 0.7309 | |
|
| 0.1781 | 43.0 | 25370 | 1.0229 | 0.7321 | |
|
| 0.1726 | 44.0 | 25960 | 0.9823 | 0.7183 | |
|
| 0.1472 | 45.0 | 26550 | 0.9605 | 0.7131 | |
|
| 0.1628 | 46.0 | 27140 | 0.9855 | 0.7382 | |
|
| 0.1658 | 47.0 | 27730 | 1.0724 | 0.7272 | |
|
| 0.1563 | 48.0 | 28320 | 0.9809 | 0.7242 | |
|
| 0.1682 | 49.0 | 28910 | 0.8878 | 0.7303 | |
|
| 0.1432 | 50.0 | 29500 | 0.9983 | 0.7324 | |
|
| 0.1437 | 51.0 | 30090 | 1.2073 | 0.6890 | |
|
| 0.1431 | 52.0 | 30680 | 1.0315 | 0.7162 | |
|
| 0.142 | 53.0 | 31270 | 1.0895 | 0.7370 | |
|
| 0.1312 | 54.0 | 31860 | 0.9904 | 0.7355 | |
|
| 0.1371 | 55.0 | 32450 | 0.9881 | 0.7159 | |
|
| 0.1383 | 56.0 | 33040 | 0.9876 | 0.7443 | |
|
| 0.128 | 57.0 | 33630 | 1.0126 | 0.7217 | |
|
| 0.1256 | 58.0 | 34220 | 0.9730 | 0.7370 | |
|
| 0.1283 | 59.0 | 34810 | 0.9943 | 0.7303 | |
|
| 0.14 | 60.0 | 35400 | 0.9945 | 0.7278 | |
|
| 0.126 | 61.0 | 35990 | 1.0015 | 0.7193 | |
|
| 0.1232 | 62.0 | 36580 | 1.0385 | 0.7190 | |
|
| 0.1163 | 63.0 | 37170 | 0.9850 | 0.7180 | |
|
| 0.1204 | 64.0 | 37760 | 1.0085 | 0.7226 | |
|
| 0.1157 | 65.0 | 38350 | 1.0784 | 0.7373 | |
|
| 0.1154 | 66.0 | 38940 | 0.9773 | 0.7330 | |
|
| 0.1101 | 67.0 | 39530 | 0.9884 | 0.7315 | |
|
| 0.1138 | 68.0 | 40120 | 0.9496 | 0.7294 | |
|
| 0.1064 | 69.0 | 40710 | 1.0320 | 0.7303 | |
|
| 0.1031 | 70.0 | 41300 | 0.9621 | 0.7327 | |
|
| 0.107 | 71.0 | 41890 | 0.9663 | 0.7349 | |
|
| 0.107 | 72.0 | 42480 | 0.9714 | 0.7309 | |
|
| 0.0958 | 73.0 | 43070 | 1.0255 | 0.7135 | |
|
| 0.0973 | 74.0 | 43660 | 0.9705 | 0.7349 | |
|
| 0.0989 | 75.0 | 44250 | 1.0003 | 0.7321 | |
|
| 0.0968 | 76.0 | 44840 | 1.0130 | 0.7306 | |
|
| 0.0947 | 77.0 | 45430 | 1.0245 | 0.7300 | |
|
| 0.0976 | 78.0 | 46020 | 1.0305 | 0.7352 | |
|
| 0.0916 | 79.0 | 46610 | 0.9644 | 0.7300 | |
|
| 0.0913 | 80.0 | 47200 | 1.0130 | 0.7373 | |
|
| 0.0911 | 81.0 | 47790 | 0.9241 | 0.7263 | |
|
| 0.0985 | 82.0 | 48380 | 0.9843 | 0.7385 | |
|
| 0.0876 | 83.0 | 48970 | 1.0069 | 0.7327 | |
|
| 0.0865 | 84.0 | 49560 | 0.9806 | 0.7303 | |
|
| 0.0872 | 85.0 | 50150 | 0.9590 | 0.7291 | |
|
| 0.0818 | 86.0 | 50740 | 0.9917 | 0.7251 | |
|
| 0.0828 | 87.0 | 51330 | 0.9569 | 0.7333 | |
|
| 0.0813 | 88.0 | 51920 | 0.9769 | 0.7260 | |
|
| 0.0763 | 89.0 | 52510 | 1.0162 | 0.7333 | |
|
| 0.0795 | 90.0 | 53100 | 0.9829 | 0.7346 | |
|
| 0.0788 | 91.0 | 53690 | 0.9755 | 0.7349 | |
|
| 0.0769 | 92.0 | 54280 | 1.0030 | 0.7315 | |
|
| 0.0739 | 93.0 | 54870 | 0.9772 | 0.7370 | |
|
| 0.0782 | 94.0 | 55460 | 0.9850 | 0.7284 | |
|
| 0.0746 | 95.0 | 56050 | 0.9688 | 0.7309 | |
|
| 0.0749 | 96.0 | 56640 | 0.9492 | 0.7309 | |
|
| 0.072 | 97.0 | 57230 | 0.9607 | 0.7303 | |
|
| 0.0693 | 98.0 | 57820 | 0.9686 | 0.7318 | |
|
| 0.0725 | 99.0 | 58410 | 0.9606 | 0.7312 | |
|
| 0.0713 | 100.0 | 59000 | 0.9505 | 0.7318 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
