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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_padding100model |
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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: 0.92944 |
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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_padding100model |
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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: 0.7393 |
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- Accuracy: 0.9294 |
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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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| 0.2387 | 1.0 | 1563 | 0.2354 | 0.919 | |
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| 0.1866 | 2.0 | 3126 | 0.2345 | 0.9248 | |
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| 0.1194 | 3.0 | 4689 | 0.3117 | 0.9212 | |
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| 0.0615 | 4.0 | 6252 | 0.3370 | 0.9219 | |
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| 0.0475 | 5.0 | 7815 | 0.5367 | 0.9131 | |
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| 0.0394 | 6.0 | 9378 | 0.5018 | 0.9236 | |
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| 0.0281 | 7.0 | 10941 | 0.5039 | 0.9243 | |
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| 0.0262 | 8.0 | 12504 | 0.5149 | 0.9238 | |
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| 0.0203 | 9.0 | 14067 | 0.5159 | 0.9275 | |
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| 0.0194 | 10.0 | 15630 | 0.5855 | 0.927 | |
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| 0.0092 | 11.0 | 17193 | 0.6452 | 0.9259 | |
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| 0.0097 | 12.0 | 18756 | 0.6318 | 0.9262 | |
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| 0.0024 | 13.0 | 20319 | 0.6537 | 0.9292 | |
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| 0.0056 | 14.0 | 21882 | 0.7551 | 0.9268 | |
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| 0.0037 | 15.0 | 23445 | 0.7516 | 0.9255 | |
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| 0.0073 | 16.0 | 25008 | 0.7335 | 0.9281 | |
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| 0.0025 | 17.0 | 26571 | 0.6959 | 0.9301 | |
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| 0.0008 | 18.0 | 28134 | 0.7439 | 0.9276 | |
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| 0.0005 | 19.0 | 29697 | 0.7300 | 0.9296 | |
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| 0.0004 | 20.0 | 31260 | 0.7393 | 0.9294 | |
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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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