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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_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: 0.93068 |
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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_padding90model |
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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: 0.7863 |
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- Accuracy: 0.9307 |
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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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| 0.2481 | 1.0 | 1563 | 0.2298 | 0.9142 | |
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| 0.1762 | 2.0 | 3126 | 0.2394 | 0.9208 | |
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| 0.1152 | 3.0 | 4689 | 0.2973 | 0.9262 | |
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| 0.0741 | 4.0 | 6252 | 0.3401 | 0.9242 | |
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| 0.0442 | 5.0 | 7815 | 0.5043 | 0.9184 | |
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| 0.04 | 6.0 | 9378 | 0.6373 | 0.9107 | |
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| 0.0258 | 7.0 | 10941 | 0.4737 | 0.9246 | |
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| 0.0199 | 8.0 | 12504 | 0.5434 | 0.9255 | |
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| 0.0198 | 9.0 | 14067 | 0.5922 | 0.9231 | |
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| 0.0122 | 10.0 | 15630 | 0.6507 | 0.924 | |
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| 0.0102 | 11.0 | 17193 | 0.6104 | 0.9274 | |
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| 0.0141 | 12.0 | 18756 | 0.6091 | 0.9267 | |
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| 0.0071 | 13.0 | 20319 | 0.6356 | 0.9255 | |
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| 0.0076 | 14.0 | 21882 | 0.6566 | 0.9296 | |
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| 0.0053 | 15.0 | 23445 | 0.6492 | 0.9296 | |
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| 0.0046 | 16.0 | 25008 | 0.7113 | 0.9284 | |
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| 0.0002 | 17.0 | 26571 | 0.7791 | 0.9286 | |
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| 0.0023 | 18.0 | 28134 | 0.7519 | 0.9308 | |
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| 0.0002 | 19.0 | 29697 | 0.7739 | 0.9303 | |
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| 0.0005 | 20.0 | 31260 | 0.7863 | 0.9307 | |
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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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