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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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model-index: |
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- name: movie-genre-predictions |
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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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# movie-genre-predictions |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9264 |
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- Accuracy: 0.3289 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 67 |
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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: 16 |
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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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| 2.1244 | 1.0 | 2318 | 2.0165 | 0.2812 | |
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| 1.8772 | 2.0 | 4636 | 1.8726 | 0.3393 | |
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| 1.7305 | 3.0 | 6954 | 1.8347 | 0.3589 | |
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| 1.5873 | 4.0 | 9272 | 1.8587 | 0.3631 | |
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| 1.4615 | 5.0 | 11590 | 1.9537 | 0.3588 | |
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| 1.2914 | 6.0 | 13908 | 2.0050 | 0.3620 | |
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| 1.15 | 7.0 | 16226 | 2.1050 | 0.3467 | |
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| 1.0332 | 8.0 | 18544 | 2.2455 | 0.3490 | |
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| 0.9257 | 9.0 | 20862 | 2.3592 | 0.3357 | |
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| 0.8086 | 10.0 | 23180 | 2.4679 | 0.3343 | |
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| 0.7231 | 11.0 | 25498 | 2.5798 | 0.3362 | |
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| 0.6471 | 12.0 | 27816 | 2.6849 | 0.3335 | |
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| 0.5839 | 13.0 | 30134 | 2.7941 | 0.3256 | |
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| 0.5238 | 14.0 | 32452 | 2.8416 | 0.3256 | |
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| 0.4804 | 15.0 | 34770 | 2.9133 | 0.3297 | |
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| 0.4346 | 16.0 | 37088 | 2.9264 | 0.3289 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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