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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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model-index: |
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- name: bert-tiny-mlm-finetuned-imdb |
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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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# bert-tiny-mlm-finetuned-imdb |
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4487 |
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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: 3e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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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: constant |
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- num_epochs: 200 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 4.1774 | 1.04 | 500 | 3.7705 | |
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| 4.041 | 2.09 | 1000 | 3.7196 | |
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| 3.9982 | 3.13 | 1500 | 3.6826 | |
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| 3.9614 | 4.18 | 2000 | 3.6543 | |
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| 3.9274 | 5.22 | 2500 | 3.6438 | |
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| 3.9089 | 6.26 | 3000 | 3.6294 | |
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| 3.8929 | 7.31 | 3500 | 3.6217 | |
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| 3.873 | 8.35 | 4000 | 3.6083 | |
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| 3.8659 | 9.39 | 4500 | 3.5900 | |
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| 3.8484 | 10.44 | 5000 | 3.5791 | |
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| 3.8261 | 11.48 | 5500 | 3.5731 | |
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| 3.8228 | 12.53 | 6000 | 3.5579 | |
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| 3.8098 | 13.57 | 6500 | 3.5576 | |
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| 3.8028 | 14.61 | 7000 | 3.5532 | |
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| 3.7881 | 15.66 | 7500 | 3.5440 | |
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| 3.7829 | 16.7 | 8000 | 3.5440 | |
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| 3.7727 | 17.75 | 8500 | 3.5372 | |
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| 3.7648 | 18.79 | 9000 | 3.5248 | |
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| 3.7504 | 19.83 | 9500 | 3.5223 | |
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| 3.7487 | 20.88 | 10000 | 3.5212 | |
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| 3.7497 | 21.92 | 10500 | 3.5166 | |
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| 3.7344 | 22.96 | 11000 | 3.5103 | |
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| 3.7339 | 24.01 | 11500 | 3.5052 | |
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| 3.722 | 25.05 | 12000 | 3.5067 | |
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| 3.7188 | 26.1 | 12500 | 3.4941 | |
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| 3.7127 | 27.14 | 13000 | 3.4951 | |
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| 3.7113 | 28.18 | 13500 | 3.4904 | |
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| 3.7042 | 29.23 | 14000 | 3.4813 | |
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| 3.7011 | 30.27 | 14500 | 3.4805 | |
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| 3.6936 | 31.32 | 15000 | 3.4886 | |
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| 3.6889 | 32.36 | 15500 | 3.4825 | |
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| 3.6771 | 33.4 | 16000 | 3.4785 | |
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| 3.6753 | 34.45 | 16500 | 3.4819 | |
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| 3.6743 | 35.49 | 17000 | 3.4744 | |
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| 3.6686 | 36.53 | 17500 | 3.4658 | |
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| 3.669 | 37.58 | 18000 | 3.4607 | |
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| 3.6623 | 38.62 | 18500 | 3.4688 | |
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| 3.6648 | 39.67 | 19000 | 3.4676 | |
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| 3.6574 | 40.71 | 19500 | 3.4581 | |
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| 3.652 | 41.75 | 20000 | 3.4601 | |
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| 3.6506 | 42.8 | 20500 | 3.4630 | |
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| 3.6466 | 43.84 | 21000 | 3.4530 | |
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| 3.637 | 44.89 | 21500 | 3.4507 | |
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| 3.6428 | 45.93 | 22000 | 3.4557 | |
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| 3.6408 | 46.97 | 22500 | 3.4483 | |
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| 3.6368 | 48.02 | 23000 | 3.4505 | |
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| 3.6322 | 49.06 | 23500 | 3.4494 | |
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| 3.6256 | 50.1 | 24000 | 3.4487 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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