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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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- crows_pairs |
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metrics: |
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- accuracy |
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model-index: |
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- name: t5-small_crows_pairs_finetuned |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: crows_pairs |
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type: crows_pairs |
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config: crows_pairs |
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split: test |
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args: crows_pairs |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6390728476821192 |
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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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# t5-small_crows_pairs_finetuned |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the crows_pairs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7111 |
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- Accuracy: 0.6391 |
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- Tp: 0.4934 |
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- Tn: 0.1457 |
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- Fp: 0.3510 |
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- Fn: 0.0099 |
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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: 0.0003 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp | Tn | Fp | Fn | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:| |
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| 0.6595 | 1.05 | 20 | 0.3672 | 0.5033 | 0.5033 | 0.0 | 0.4967 | 0.0 | |
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| 0.4048 | 2.11 | 40 | 0.3723 | 0.5033 | 0.5033 | 0.0 | 0.4967 | 0.0 | |
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| 0.3397 | 3.16 | 60 | 0.3397 | 0.5033 | 0.5033 | 0.0 | 0.4967 | 0.0 | |
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| 0.3215 | 4.21 | 80 | 0.3227 | 0.5132 | 0.5033 | 0.0099 | 0.4868 | 0.0 | |
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| 0.3078 | 5.26 | 100 | 0.3381 | 0.6060 | 0.5033 | 0.1026 | 0.3940 | 0.0 | |
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| 0.2258 | 6.32 | 120 | 0.3012 | 0.5629 | 0.5 | 0.0629 | 0.4338 | 0.0033 | |
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| 0.2099 | 7.37 | 140 | 0.3018 | 0.5894 | 0.5 | 0.0894 | 0.4073 | 0.0033 | |
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| 0.1531 | 8.42 | 160 | 0.3379 | 0.5464 | 0.5033 | 0.0430 | 0.4536 | 0.0 | |
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| 0.129 | 9.47 | 180 | 0.3602 | 0.5993 | 0.5 | 0.0993 | 0.3974 | 0.0033 | |
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| 0.0956 | 10.53 | 200 | 0.3846 | 0.5762 | 0.5 | 0.0762 | 0.4205 | 0.0033 | |
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| 0.0736 | 11.58 | 220 | 0.4245 | 0.5695 | 0.5033 | 0.0662 | 0.4305 | 0.0 | |
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| 0.0474 | 12.63 | 240 | 0.4938 | 0.5695 | 0.5033 | 0.0662 | 0.4305 | 0.0 | |
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| 0.0369 | 13.68 | 260 | 0.5201 | 0.5960 | 0.5 | 0.0960 | 0.4007 | 0.0033 | |
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| 0.0323 | 14.74 | 280 | 0.5559 | 0.5993 | 0.4934 | 0.1060 | 0.3907 | 0.0099 | |
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| 0.0267 | 15.79 | 300 | 0.5965 | 0.5894 | 0.5 | 0.0894 | 0.4073 | 0.0033 | |
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| 0.026 | 16.84 | 320 | 0.6052 | 0.5960 | 0.4967 | 0.0993 | 0.3974 | 0.0066 | |
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| 0.0194 | 17.89 | 340 | 0.6144 | 0.6126 | 0.4934 | 0.1192 | 0.3775 | 0.0099 | |
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| 0.0242 | 18.95 | 360 | 0.6286 | 0.6126 | 0.4934 | 0.1192 | 0.3775 | 0.0099 | |
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| 0.0274 | 20.0 | 380 | 0.6313 | 0.6325 | 0.4901 | 0.1424 | 0.3543 | 0.0132 | |
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| 0.0151 | 21.05 | 400 | 0.6685 | 0.6192 | 0.4934 | 0.1258 | 0.3709 | 0.0099 | |
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| 0.0131 | 22.11 | 420 | 0.6815 | 0.6258 | 0.4934 | 0.1325 | 0.3642 | 0.0099 | |
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| 0.0095 | 23.16 | 440 | 0.6961 | 0.6192 | 0.4967 | 0.1225 | 0.3742 | 0.0066 | |
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| 0.0064 | 24.21 | 460 | 0.6980 | 0.6325 | 0.4934 | 0.1391 | 0.3576 | 0.0099 | |
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| 0.0103 | 25.26 | 480 | 0.7117 | 0.6192 | 0.4934 | 0.1258 | 0.3709 | 0.0099 | |
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| 0.0083 | 26.32 | 500 | 0.7096 | 0.6258 | 0.4934 | 0.1325 | 0.3642 | 0.0099 | |
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| 0.0079 | 27.37 | 520 | 0.7198 | 0.6258 | 0.4934 | 0.1325 | 0.3642 | 0.0099 | |
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| 0.01 | 28.42 | 540 | 0.7210 | 0.6258 | 0.4934 | 0.1325 | 0.3642 | 0.0099 | |
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| 0.011 | 29.47 | 560 | 0.7111 | 0.6391 | 0.4934 | 0.1457 | 0.3510 | 0.0099 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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