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--- |
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library_name: transformers |
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base_model: sandernotenbaert/okai-musiclang-content-t5-small_finetune |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: okai-musiclang-content-t5-small_finetune |
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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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# okai-musiclang-content-t5-small_finetune |
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This model is a fine-tuned version of [sandernotenbaert/okai-musiclang-content-t5-small_finetune](https://huggingface.co/sandernotenbaert/okai-musiclang-content-t5-small_finetune) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5041 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Use OptimizerNames.ADAFACTOR and the args are: |
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No additional optimizer arguments |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_ratio: 0.02 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 1.7839 | 0.2226 | 500 | 1.6513 | |
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| 1.6576 | 0.4452 | 1000 | 1.6615 | |
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| 1.6396 | 0.6679 | 1500 | 1.6650 | |
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| 1.7168 | 0.8905 | 2000 | 1.6315 | |
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| 1.7366 | 1.1131 | 2500 | 1.6234 | |
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| 1.7171 | 1.3357 | 3000 | 1.6028 | |
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| 1.6238 | 1.5583 | 3500 | 1.6130 | |
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| 1.6217 | 1.7810 | 4000 | 1.6218 | |
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| 1.7077 | 2.0036 | 4500 | 1.5784 | |
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| 1.7034 | 2.2262 | 5000 | 1.5792 | |
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| 1.6049 | 2.4488 | 5500 | 1.5866 | |
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| 1.6018 | 2.6714 | 6000 | 1.5869 | |
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| 1.6628 | 2.8941 | 6500 | 1.5628 | |
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| 1.653 | 3.1171 | 7000 | 1.5606 | |
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| 1.6575 | 3.3397 | 7500 | 1.5381 | |
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| 1.64 | 3.5619 | 8000 | 1.5395 | |
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| 1.6455 | 3.7845 | 8500 | 1.5163 | |
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| 1.6308 | 4.0076 | 9000 | 1.5311 | |
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| 1.6324 | 4.2302 | 9500 | 1.5118 | |
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| 1.5481 | 4.4528 | 10000 | 1.5092 | |
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| 1.547 | 4.6754 | 10500 | 1.5109 | |
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| 1.5584 | 4.8981 | 11000 | 1.5041 | |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
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