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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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- music |
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metrics: |
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- accuracy |
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datasets: |
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- sandernotenbaert/lmd_matched |
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training_config: |
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vocab_size: 30000 |
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hidden_size: 256 |
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intermediate_size: 512 |
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num_hidden_layers: 4 |
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num_attention_heads: 4 |
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num_key_value_heads: 4 |
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sliding_window: 4 |
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max_position_embeddings: 1024 |
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pad_token_id: 0 |
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bos_token_id: 1 |
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eos_token_id: 2 |
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pipeline_tag: other |
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model-index: |
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- name: OKAI-midi-gen-v-001 |
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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-midi-gen-v-001 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 10.1912 |
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- Accuracy: 0.0008 |
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## Model description |
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First test with small subset on M1Pro. Generates valid files, notes very clustered with long gaps |
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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_config: |
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vocab_size: 30000 |
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hidden_size: 256 |
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intermediate_size: 512 |
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num_hidden_layers: 4 |
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num_attention_heads: 4 |
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num_key_value_heads: 4 |
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sliding_window: 4 |
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max_position_embeddings: 1024 |
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pad_token_id: 0 |
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bos_token_id: 1 |
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eos_token_id: 2 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 444 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 24 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.3 |
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- training_steps: 2000 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-------:|:----:|:--------:|:---------------:| |
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| 10.2727 | 3.2283 | 100 | 0.0000 | 10.3284 | |
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| 9.7582 | 6.4565 | 200 | 0.0026 | 10.0966 | |
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| 9.2052 | 9.6848 | 300 | 0.0037 | 9.9513 | |
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| 8.8216 | 12.9130 | 400 | 0.0034 | 9.9538 | |
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| 8.406 | 16.1304 | 500 | 0.0029 | 9.9524 | |
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| 7.8326 | 19.3587 | 600 | 0.0021 | 9.9458 | |
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| 7.1956 | 22.5870 | 700 | 0.0017 | 9.9864 | |
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| 6.5659 | 25.8152 | 800 | 0.0015 | 9.9258 | |
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| 5.9719 | 29.0326 | 900 | 0.0015 | 9.9710 | |
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| 5.4031 | 32.2609 | 1000 | 0.0011 | 9.9116 | |
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| 4.9784 | 35.4891 | 1100 | 0.0012 | 9.9819 | |
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| 4.6684 | 38.7174 | 1200 | 0.0009 | 10.0142 | |
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| 4.3184 | 41.9783 | 1300 | 10.0483 | 0.0010 | |
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| 4.1251 | 45.1957 | 1400 | 10.0964 | 0.0008 | |
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| 3.909 | 48.4239 | 1500 | 10.1322 | 0.0009 | |
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| 3.7535 | 51.6522 | 1600 | 10.1587 | 0.0009 | |
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| 3.681 | 54.8804 | 1700 | 10.1785 | 0.0008 | |
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| 3.688 | 58.0978 | 1800 | 10.1871 | 0.0008 | |
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| 3.6685 | 61.3261 | 1900 | 10.1912 | 0.0008 | |
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| 3.6326 | 64.5543 | 2000 | 10.1912 | 0.0008 | |
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### Framework versions |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
