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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: '20230823013619' |
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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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# 20230823013619 |
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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: 0.0007 |
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- Accuracy: 0.4729 |
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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: 0.003 |
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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: 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 | 156 | 0.0076 | 0.5199 | |
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| No log | 2.0 | 312 | 0.0418 | 0.5343 | |
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| No log | 3.0 | 468 | 0.0044 | 0.5054 | |
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| 0.0669 | 4.0 | 624 | 0.0117 | 0.4693 | |
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| 0.0669 | 5.0 | 780 | 0.0333 | 0.4729 | |
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| 0.0669 | 6.0 | 936 | 0.0014 | 0.4693 | |
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| 0.0209 | 7.0 | 1092 | 0.0008 | 0.4729 | |
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| 0.0209 | 8.0 | 1248 | 0.0031 | 0.4729 | |
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| 0.0209 | 9.0 | 1404 | 0.0049 | 0.4982 | |
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| 0.0144 | 10.0 | 1560 | 0.0007 | 0.4729 | |
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| 0.0144 | 11.0 | 1716 | 0.0014 | 0.4693 | |
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| 0.0144 | 12.0 | 1872 | 0.0022 | 0.5054 | |
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| 0.0094 | 13.0 | 2028 | 0.0008 | 0.4729 | |
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| 0.0094 | 14.0 | 2184 | 0.0012 | 0.4729 | |
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| 0.0094 | 15.0 | 2340 | 0.0018 | 0.4729 | |
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| 0.0094 | 16.0 | 2496 | 0.0008 | 0.4729 | |
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| 0.0087 | 17.0 | 2652 | 0.0011 | 0.4729 | |
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| 0.0087 | 18.0 | 2808 | 0.0009 | 0.4729 | |
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| 0.0087 | 19.0 | 2964 | 0.0010 | 0.4729 | |
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| 0.0091 | 20.0 | 3120 | 0.0021 | 0.4585 | |
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| 0.0091 | 21.0 | 3276 | 0.0008 | 0.4729 | |
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| 0.0091 | 22.0 | 3432 | 0.0010 | 0.4729 | |
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| 0.0087 | 23.0 | 3588 | 0.0007 | 0.4729 | |
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| 0.0087 | 24.0 | 3744 | 0.0012 | 0.4765 | |
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| 0.0087 | 25.0 | 3900 | 0.0013 | 0.4729 | |
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| 0.0088 | 26.0 | 4056 | 0.0010 | 0.4910 | |
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| 0.0088 | 27.0 | 4212 | 0.0012 | 0.4765 | |
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| 0.0088 | 28.0 | 4368 | 0.0012 | 0.4729 | |
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| 0.0087 | 29.0 | 4524 | 0.0013 | 0.4910 | |
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| 0.0087 | 30.0 | 4680 | 0.0009 | 0.4729 | |
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| 0.0087 | 31.0 | 4836 | 0.0012 | 0.4729 | |
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| 0.0087 | 32.0 | 4992 | 0.0007 | 0.4729 | |
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| 0.0089 | 33.0 | 5148 | 0.0009 | 0.4729 | |
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| 0.0089 | 34.0 | 5304 | 0.0008 | 0.4729 | |
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| 0.0089 | 35.0 | 5460 | 0.0007 | 0.4729 | |
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| 0.0087 | 36.0 | 5616 | 0.0009 | 0.4729 | |
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| 0.0087 | 37.0 | 5772 | 0.0007 | 0.4801 | |
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| 0.0087 | 38.0 | 5928 | 0.0007 | 0.4729 | |
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| 0.0093 | 39.0 | 6084 | 0.0007 | 0.4729 | |
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| 0.0093 | 40.0 | 6240 | 0.0008 | 0.4729 | |
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| 0.0093 | 41.0 | 6396 | 0.0011 | 0.4729 | |
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| 0.0086 | 42.0 | 6552 | 0.0008 | 0.4729 | |
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| 0.0086 | 43.0 | 6708 | 0.0017 | 0.4729 | |
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| 0.0086 | 44.0 | 6864 | 0.0009 | 0.4729 | |
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| 0.0085 | 45.0 | 7020 | 0.0007 | 0.4729 | |
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| 0.0085 | 46.0 | 7176 | 0.0022 | 0.4729 | |
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| 0.0085 | 47.0 | 7332 | 0.0009 | 0.4729 | |
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| 0.0085 | 48.0 | 7488 | 0.0008 | 0.4729 | |
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| 0.0087 | 49.0 | 7644 | 0.0007 | 0.4729 | |
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| 0.0087 | 50.0 | 7800 | 0.0010 | 0.4729 | |
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| 0.0087 | 51.0 | 7956 | 0.0007 | 0.4729 | |
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| 0.0084 | 52.0 | 8112 | 0.0013 | 0.4729 | |
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| 0.0084 | 53.0 | 8268 | 0.0010 | 0.4729 | |
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| 0.0084 | 54.0 | 8424 | 0.0010 | 0.4729 | |
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| 0.0083 | 55.0 | 8580 | 0.0007 | 0.4729 | |
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| 0.0083 | 56.0 | 8736 | 0.0007 | 0.4729 | |
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| 0.0083 | 57.0 | 8892 | 0.0007 | 0.4729 | |
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| 0.0082 | 58.0 | 9048 | 0.0007 | 0.4729 | |
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| 0.0082 | 59.0 | 9204 | 0.0007 | 0.4729 | |
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| 0.0082 | 60.0 | 9360 | 0.0007 | 0.4729 | |
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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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