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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: midi_model_3 |
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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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# midi_model_3 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5542 |
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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: 0.0005 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 1 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8047 | 0.33 | 300 | 0.7969 | |
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| 0.7924 | 0.66 | 600 | 0.7735 | |
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| 0.7758 | 1.0 | 900 | 0.7528 | |
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| 0.75 | 1.33 | 1200 | 0.7436 | |
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| 0.7432 | 1.66 | 1500 | 0.7277 | |
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| 0.7361 | 1.99 | 1800 | 0.7175 | |
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| 0.7121 | 2.32 | 2100 | 0.7025 | |
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| 0.708 | 2.65 | 2400 | 0.6861 | |
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| 0.6971 | 2.99 | 2700 | 0.6781 | |
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| 0.6777 | 3.32 | 3000 | 0.6718 | |
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| 0.6733 | 3.65 | 3300 | 0.6578 | |
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| 0.6643 | 3.98 | 3600 | 0.6500 | |
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| 0.6422 | 4.31 | 3900 | 0.6423 | |
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| 0.6401 | 4.65 | 4200 | 0.6330 | |
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| 0.6302 | 4.98 | 4500 | 0.6228 | |
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| 0.6103 | 5.31 | 4800 | 0.6148 | |
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| 0.6066 | 5.64 | 5100 | 0.6069 | |
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| 0.5995 | 5.97 | 5400 | 0.5979 | |
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| 0.5724 | 6.31 | 5700 | 0.5915 | |
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| 0.5772 | 6.64 | 6000 | 0.5870 | |
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| 0.5677 | 6.97 | 6300 | 0.5771 | |
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| 0.5491 | 7.3 | 6600 | 0.5740 | |
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| 0.5433 | 7.63 | 6900 | 0.5675 | |
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| 0.5384 | 7.96 | 7200 | 0.5630 | |
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| 0.5245 | 8.3 | 7500 | 0.5611 | |
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| 0.5206 | 8.63 | 7800 | 0.5578 | |
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| 0.5198 | 8.96 | 8100 | 0.5553 | |
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| 0.5141 | 9.29 | 8400 | 0.5544 | |
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| 0.5091 | 9.62 | 8700 | 0.5543 | |
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| 0.5096 | 9.96 | 9000 | 0.5542 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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