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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- sibyl |
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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: bert-base-uncased-imdb |
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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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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: 0.91264 |
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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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# bert-base-uncased-imdb |
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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: 0.4942 |
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- Accuracy: 0.9126 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 1546 |
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- training_steps: 15468 |
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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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| 0.3952 | 0.65 | 2000 | 0.4012 | 0.86 | |
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| 0.2954 | 1.29 | 4000 | 0.4535 | 0.892 | |
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| 0.2595 | 1.94 | 6000 | 0.4320 | 0.892 | |
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| 0.1516 | 2.59 | 8000 | 0.5309 | 0.896 | |
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| 0.1167 | 3.23 | 10000 | 0.4070 | 0.928 | |
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| 0.0624 | 3.88 | 12000 | 0.5055 | 0.908 | |
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| 0.0329 | 4.52 | 14000 | 0.4342 | 0.92 | |
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### Framework versions |
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- Transformers 4.10.2 |
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- Pytorch 1.7.1 |
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- Datasets 1.6.1 |
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- Tokenizers 0.10.3 |
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