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--- |
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license: apache-2.0 |
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base_model: distilbert-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_distilbert_imdb_padding50model |
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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: 0.93268 |
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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_distilbert_imdb_padding50model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7391 |
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- Accuracy: 0.9327 |
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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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| 0.2431 | 1.0 | 1563 | 0.2690 | 0.9089 | |
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| 0.1734 | 2.0 | 3126 | 0.2418 | 0.9260 | |
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| 0.1167 | 3.0 | 4689 | 0.4345 | 0.9078 | |
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| 0.0685 | 4.0 | 6252 | 0.3717 | 0.926 | |
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| 0.0445 | 5.0 | 7815 | 0.4502 | 0.9242 | |
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| 0.0338 | 6.0 | 9378 | 0.4786 | 0.9287 | |
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| 0.0293 | 7.0 | 10941 | 0.5332 | 0.9214 | |
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| 0.0191 | 8.0 | 12504 | 0.5435 | 0.9287 | |
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| 0.0182 | 9.0 | 14067 | 0.5450 | 0.9265 | |
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| 0.015 | 10.0 | 15630 | 0.5398 | 0.9297 | |
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| 0.0122 | 11.0 | 17193 | 0.6565 | 0.9226 | |
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| 0.0089 | 12.0 | 18756 | 0.6521 | 0.9280 | |
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| 0.0081 | 13.0 | 20319 | 0.6755 | 0.9285 | |
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| 0.0067 | 14.0 | 21882 | 0.6753 | 0.93 | |
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| 0.0054 | 15.0 | 23445 | 0.7014 | 0.9305 | |
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| 0.0023 | 16.0 | 25008 | 0.7440 | 0.9308 | |
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| 0.0004 | 17.0 | 26571 | 0.7371 | 0.9286 | |
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| 0.0 | 18.0 | 28134 | 0.7497 | 0.9302 | |
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| 0.0004 | 19.0 | 29697 | 0.7386 | 0.9324 | |
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| 0.0002 | 20.0 | 31260 | 0.7391 | 0.9327 | |
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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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