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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert-base-uncased-finetuned-sst-2-english |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: imdb |
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results: [] |
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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 |
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This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2032 |
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- Accuracy: 0.927 |
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- Precision: 0.9241 |
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- Recall: 0.9318 |
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- F1: 0.9280 |
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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-06 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.2612 | 1.0 | 625 | 0.2290 | 0.9122 | 0.9080 | 0.9191 | 0.9135 | |
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| 0.218 | 2.0 | 1250 | 0.2174 | 0.919 | 0.9114 | 0.9298 | 0.9205 | |
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| 0.2019 | 3.0 | 1875 | 0.2120 | 0.922 | 0.9197 | 0.9263 | 0.9230 | |
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| 0.1806 | 4.0 | 2500 | 0.2070 | 0.9214 | 0.9122 | 0.9342 | 0.9230 | |
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| 0.1711 | 5.0 | 3125 | 0.2052 | 0.9244 | 0.9191 | 0.9322 | 0.9256 | |
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| 0.1605 | 6.0 | 3750 | 0.2032 | 0.9236 | 0.9164 | 0.9338 | 0.9250 | |
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| 0.1639 | 7.0 | 4375 | 0.2062 | 0.9244 | 0.9152 | 0.9370 | 0.9260 | |
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| 0.1544 | 8.0 | 5000 | 0.2026 | 0.9268 | 0.9265 | 0.9287 | 0.9276 | |
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| 0.148 | 9.0 | 5625 | 0.2035 | 0.9274 | 0.9212 | 0.9362 | 0.9286 | |
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| 0.144 | 10.0 | 6250 | 0.2032 | 0.927 | 0.9241 | 0.9318 | 0.9280 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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