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--- |
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language: |
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- en |
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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: imdb_distilbert-base-uncased |
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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: imdb |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.87736 |
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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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# imdb_distilbert-base-uncased |
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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: 0.2911 |
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- Accuracy: 0.8774 |
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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: 64 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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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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| 0.6487 | 0.2 | 78 | 0.4402 | 0.8117 | |
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| 0.402 | 0.4 | 156 | 0.3563 | 0.8416 | |
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| 0.3528 | 0.6 | 234 | 0.3522 | 0.8434 | |
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| 0.3362 | 0.8 | 312 | 0.3099 | 0.8652 | |
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| 0.3184 | 1.0 | 390 | 0.3028 | 0.8700 | |
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| 0.265 | 1.2 | 468 | 0.3052 | 0.8738 | |
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| 0.2593 | 1.4 | 546 | 0.2983 | 0.8735 | |
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| 0.2537 | 1.6 | 624 | 0.2977 | 0.8754 | |
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| 0.2558 | 1.8 | 702 | 0.2911 | 0.8774 | |
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| 0.2476 | 1.99 | 780 | 0.2907 | 0.8751 | |
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| 0.1941 | 2.19 | 858 | 0.3151 | 0.8774 | |
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| 0.1873 | 2.39 | 936 | 0.3104 | 0.8764 | |
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| 0.1869 | 2.59 | 1014 | 0.3181 | 0.8771 | |
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| 0.1807 | 2.79 | 1092 | 0.3148 | 0.8764 | |
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| 0.1967 | 2.99 | 1170 | 0.3141 | 0.8766 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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