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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- generator |
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model-index: |
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- name: MIDICausalFinetuningFromFolder |
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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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# MIDICausalFinetuningFromFolder |
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This model was trained from scratch on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1183 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 30 |
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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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| 2.6992 | 1.0 | 959 | 2.6253 | |
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| 2.6438 | 2.0 | 1918 | 2.5918 | |
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| 2.6098 | 3.0 | 2877 | 2.5617 | |
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| 2.5847 | 4.0 | 3836 | 2.5325 | |
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| 2.5604 | 5.0 | 4795 | 2.5040 | |
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| 2.5433 | 6.0 | 5754 | 2.4798 | |
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| 2.5203 | 7.0 | 6713 | 2.4534 | |
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| 2.4956 | 8.0 | 7672 | 2.4253 | |
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| 2.4787 | 9.0 | 8631 | 2.4038 | |
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| 2.4582 | 10.0 | 9590 | 2.3793 | |
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| 2.4419 | 11.0 | 10549 | 2.3574 | |
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| 2.4246 | 12.0 | 11508 | 2.3354 | |
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| 2.4114 | 13.0 | 12467 | 2.3144 | |
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| 2.3916 | 14.0 | 13426 | 2.2958 | |
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| 2.3882 | 15.0 | 14385 | 2.2784 | |
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| 2.364 | 16.0 | 15344 | 2.2607 | |
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| 2.3512 | 17.0 | 16303 | 2.2440 | |
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| 2.3444 | 18.0 | 17262 | 2.2292 | |
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| 2.3261 | 19.0 | 18221 | 2.2123 | |
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| 2.3165 | 20.0 | 19180 | 2.1988 | |
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| 2.3071 | 21.0 | 20139 | 2.1844 | |
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| 2.2968 | 22.0 | 21098 | 2.1729 | |
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| 2.2868 | 23.0 | 22057 | 2.1625 | |
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| 2.2777 | 24.0 | 23016 | 2.1522 | |
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| 2.2666 | 25.0 | 23975 | 2.1428 | |
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| 2.2619 | 26.0 | 24934 | 2.1365 | |
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| 2.2616 | 27.0 | 25893 | 2.1291 | |
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| 2.2563 | 28.0 | 26852 | 2.1228 | |
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| 2.2482 | 29.0 | 27811 | 2.1197 | |
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| 2.2493 | 30.0 | 28770 | 2.1183 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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