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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: '20230816190102' |
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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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# 20230816190102 |
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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: 0.3431 |
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- Accuracy: 0.7004 |
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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: 8 |
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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: 60.0 |
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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 | 312 | 0.5884 | 0.5235 | |
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| 0.6001 | 2.0 | 624 | 0.4145 | 0.4729 | |
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| 0.6001 | 3.0 | 936 | 0.6337 | 0.4729 | |
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| 0.5343 | 4.0 | 1248 | 0.3934 | 0.4838 | |
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| 0.5255 | 5.0 | 1560 | 0.5662 | 0.4729 | |
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| 0.5255 | 6.0 | 1872 | 0.5158 | 0.5271 | |
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| 0.504 | 7.0 | 2184 | 0.3480 | 0.5343 | |
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| 0.504 | 8.0 | 2496 | 0.3846 | 0.5379 | |
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| 0.4941 | 9.0 | 2808 | 0.5111 | 0.5307 | |
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| 0.5022 | 10.0 | 3120 | 0.4621 | 0.5271 | |
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| 0.5022 | 11.0 | 3432 | 0.3418 | 0.6426 | |
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| 0.453 | 12.0 | 3744 | 0.3652 | 0.5632 | |
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| 0.3879 | 13.0 | 4056 | 0.3451 | 0.5596 | |
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| 0.3879 | 14.0 | 4368 | 0.3312 | 0.6426 | |
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| 0.3698 | 15.0 | 4680 | 0.3599 | 0.6462 | |
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| 0.3698 | 16.0 | 4992 | 0.3947 | 0.5993 | |
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| 0.3705 | 17.0 | 5304 | 0.3833 | 0.6173 | |
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| 0.3598 | 18.0 | 5616 | 0.3354 | 0.6462 | |
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| 0.3598 | 19.0 | 5928 | 0.3395 | 0.6715 | |
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| 0.3631 | 20.0 | 6240 | 0.3664 | 0.6390 | |
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| 0.3515 | 21.0 | 6552 | 0.3420 | 0.6787 | |
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| 0.3515 | 22.0 | 6864 | 0.3483 | 0.6137 | |
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| 0.3486 | 23.0 | 7176 | 0.3820 | 0.6498 | |
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| 0.3486 | 24.0 | 7488 | 0.3240 | 0.7004 | |
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| 0.3437 | 25.0 | 7800 | 0.3300 | 0.7148 | |
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| 0.3389 | 26.0 | 8112 | 0.3405 | 0.6787 | |
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| 0.3389 | 27.0 | 8424 | 0.3291 | 0.6968 | |
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| 0.3363 | 28.0 | 8736 | 0.3338 | 0.6895 | |
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| 0.3381 | 29.0 | 9048 | 0.3366 | 0.7220 | |
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| 0.3381 | 30.0 | 9360 | 0.3831 | 0.6606 | |
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| 0.3302 | 31.0 | 9672 | 0.3300 | 0.7040 | |
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| 0.3302 | 32.0 | 9984 | 0.3224 | 0.7040 | |
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| 0.33 | 33.0 | 10296 | 0.3332 | 0.6787 | |
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| 0.3271 | 34.0 | 10608 | 0.3412 | 0.7256 | |
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| 0.3271 | 35.0 | 10920 | 0.3197 | 0.7076 | |
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| 0.3266 | 36.0 | 11232 | 0.3236 | 0.7148 | |
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| 0.3248 | 37.0 | 11544 | 0.3621 | 0.6751 | |
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| 0.3248 | 38.0 | 11856 | 0.3330 | 0.7040 | |
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| 0.3223 | 39.0 | 12168 | 0.3636 | 0.6823 | |
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| 0.3223 | 40.0 | 12480 | 0.3298 | 0.7076 | |
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| 0.3205 | 41.0 | 12792 | 0.3224 | 0.7148 | |
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| 0.3177 | 42.0 | 13104 | 0.3288 | 0.7256 | |
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| 0.3177 | 43.0 | 13416 | 0.3464 | 0.6823 | |
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| 0.3167 | 44.0 | 13728 | 0.3567 | 0.6787 | |
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| 0.3159 | 45.0 | 14040 | 0.3551 | 0.6895 | |
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| 0.3159 | 46.0 | 14352 | 0.3313 | 0.7112 | |
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| 0.3131 | 47.0 | 14664 | 0.3233 | 0.7292 | |
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| 0.3131 | 48.0 | 14976 | 0.3508 | 0.6751 | |
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| 0.3118 | 49.0 | 15288 | 0.3420 | 0.7040 | |
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| 0.3088 | 50.0 | 15600 | 0.3410 | 0.6968 | |
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| 0.3088 | 51.0 | 15912 | 0.3421 | 0.7040 | |
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| 0.3082 | 52.0 | 16224 | 0.3411 | 0.7040 | |
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| 0.3068 | 53.0 | 16536 | 0.3616 | 0.6823 | |
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| 0.3068 | 54.0 | 16848 | 0.3555 | 0.6715 | |
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| 0.3031 | 55.0 | 17160 | 0.3418 | 0.7004 | |
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| 0.3031 | 56.0 | 17472 | 0.3460 | 0.6859 | |
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| 0.3039 | 57.0 | 17784 | 0.3353 | 0.7148 | |
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| 0.3025 | 58.0 | 18096 | 0.3450 | 0.7004 | |
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| 0.3025 | 59.0 | 18408 | 0.3427 | 0.7040 | |
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| 0.3034 | 60.0 | 18720 | 0.3431 | 0.7004 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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