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update model card README.md
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README.md
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---
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base_model: juancopi81/lmd-8bars-2048-epochs30_v4
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tags:
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- generated_from_trainer
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model-index:
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- name: lmd-8bars-2048-epochs40_v4
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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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# lmd-8bars-2048-epochs40_v4
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This model is a fine-tuned version of [juancopi81/lmd-8bars-2048-epochs30_v4](https://huggingface.co/juancopi81/lmd-8bars-2048-epochs30_v4) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9128
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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: 8
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- eval_batch_size: 4
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- seed: 1
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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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| 0.959 | 0.5 | 4994 | 0.9735 |
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| 0.9841 | 1.0 | 9988 | 0.9691 |
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| 0.9779 | 1.5 | 14982 | 0.9632 |
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| 0.9818 | 2.0 | 19976 | 0.9590 |
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| 0.9736 | 2.5 | 24970 | 0.9610 |
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| 0.9715 | 3.0 | 29964 | 0.9552 |
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| 0.9629 | 3.5 | 34958 | 0.9520 |
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| 0.9623 | 4.0 | 39952 | 0.9435 |
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| 0.9509 | 4.5 | 44946 | 0.9442 |
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| 0.9499 | 5.0 | 49940 | 0.9404 |
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| 0.9367 | 5.5 | 54934 | 0.9334 |
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| 0.9376 | 6.0 | 59928 | 0.9308 |
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| 0.9247 | 6.5 | 64922 | 0.9270 |
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| 0.9255 | 7.0 | 69916 | 0.9200 |
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| 0.9163 | 7.5 | 74910 | 0.9184 |
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| 0.9123 | 8.0 | 79904 | 0.9160 |
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| 0.9071 | 8.5 | 84898 | 0.9147 |
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| 0.9042 | 9.0 | 89892 | 0.9132 |
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| 0.9026 | 9.5 | 94886 | 0.9124 |
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| 0.9012 | 10.0 | 99880 | 0.9128 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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