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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_padding10model |
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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: 0.93976 |
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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_padding10model |
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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: 0.6695 |
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- Accuracy: 0.9398 |
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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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| 0.2175 | 1.0 | 1563 | 0.2147 | 0.9269 | |
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| 0.1483 | 2.0 | 3126 | 0.2123 | 0.9384 | |
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| 0.0912 | 3.0 | 4689 | 0.2707 | 0.9325 | |
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| 0.0569 | 4.0 | 6252 | 0.3262 | 0.9314 | |
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| 0.042 | 5.0 | 7815 | 0.3316 | 0.9372 | |
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| 0.0373 | 6.0 | 9378 | 0.4147 | 0.9365 | |
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| 0.0181 | 7.0 | 10941 | 0.4632 | 0.936 | |
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| 0.0144 | 8.0 | 12504 | 0.5192 | 0.9338 | |
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| 0.0138 | 9.0 | 14067 | 0.4934 | 0.9388 | |
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| 0.0094 | 10.0 | 15630 | 0.5627 | 0.9363 | |
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| 0.0091 | 11.0 | 17193 | 0.6356 | 0.9285 | |
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| 0.0114 | 12.0 | 18756 | 0.5780 | 0.9368 | |
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| 0.0025 | 13.0 | 20319 | 0.6362 | 0.9402 | |
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| 0.0067 | 14.0 | 21882 | 0.5902 | 0.9388 | |
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| 0.0043 | 15.0 | 23445 | 0.6124 | 0.9387 | |
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| 0.0029 | 16.0 | 25008 | 0.5929 | 0.9380 | |
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| 0.0001 | 17.0 | 26571 | 0.6554 | 0.9394 | |
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| 0.0005 | 18.0 | 28134 | 0.6619 | 0.9408 | |
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| 0.0019 | 19.0 | 29697 | 0.6654 | 0.9398 | |
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| 0.0 | 20.0 | 31260 | 0.6695 | 0.9398 | |
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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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