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