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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imdb |
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metrics: |
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- accuracy |
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model-index: |
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- name: N_bert_imdb_padding90model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: imdb |
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type: imdb |
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config: plain_text |
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split: test |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.93696 |
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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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# N_bert_imdb_padding90model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6812 |
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- Accuracy: 0.9370 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 20 |
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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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| 0.231 | 1.0 | 1563 | 0.2247 | 0.9244 | |
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| 0.1494 | 2.0 | 3126 | 0.2082 | 0.9327 | |
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| 0.0859 | 3.0 | 4689 | 0.3046 | 0.9325 | |
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| 0.0543 | 4.0 | 6252 | 0.3399 | 0.9306 | |
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| 0.0426 | 5.0 | 7815 | 0.4251 | 0.9296 | |
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| 0.0382 | 6.0 | 9378 | 0.4925 | 0.9283 | |
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| 0.0239 | 7.0 | 10941 | 0.5281 | 0.9283 | |
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| 0.0175 | 8.0 | 12504 | 0.4922 | 0.9323 | |
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| 0.0161 | 9.0 | 14067 | 0.5648 | 0.9324 | |
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| 0.0091 | 10.0 | 15630 | 0.5808 | 0.9366 | |
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| 0.0139 | 11.0 | 17193 | 0.5845 | 0.9345 | |
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| 0.0041 | 12.0 | 18756 | 0.5509 | 0.9330 | |
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| 0.0055 | 13.0 | 20319 | 0.6335 | 0.9342 | |
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| 0.0019 | 14.0 | 21882 | 0.6713 | 0.9356 | |
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| 0.0024 | 15.0 | 23445 | 0.6316 | 0.9358 | |
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| 0.0 | 16.0 | 25008 | 0.6567 | 0.9379 | |
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| 0.0038 | 17.0 | 26571 | 0.6668 | 0.9375 | |
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| 0.0009 | 18.0 | 28134 | 0.6795 | 0.9373 | |
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| 0.0013 | 19.0 | 29697 | 0.6736 | 0.9371 | |
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| 0.0001 | 20.0 | 31260 | 0.6812 | 0.9370 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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