| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imdb |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: finetuning-sentiment-model-3000-samples-DM |
| results: |
| - task: |
| name: Text Classification |
| type: text-classification |
| dataset: |
| name: imdb |
| type: imdb |
| args: plain_text |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8666666666666667 |
| - name: F1 |
| type: f1 |
| value: 0.8734177215189873 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # finetuning-sentiment-model-3000-samples-DM |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3248 |
| - Accuracy: 0.8667 |
| - F1: 0.8734 |
|
|
| ## 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: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
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| ### Training results |
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| ### Framework versions |
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|
| - Transformers 4.19.2 |
| - Pytorch 1.8.0 |
| - Datasets 2.2.2 |
| - Tokenizers 0.12.1 |
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