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---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- acordes_completo
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-chorddetection2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilhubert-finetuned-chorddetection2
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the ChordStimation2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4498 | 1.0 | 3025 | 0.4276 | 0.9367 |
| 0.0007 | 2.0 | 6050 | 0.0389 | 0.9899 |
| 0.119 | 3.0 | 9075 | 0.0704 | 0.9863 |
| 0.0 | 4.0 | 12100 | 0.0000 | 1.0 |
| 0.0 | 5.0 | 15125 | 0.0000 | 1.0 |
| 0.0 | 6.0 | 18150 | 0.0004 | 1.0 |
| 0.0 | 7.0 | 21175 | 0.0009 | 0.9998 |
| 0.0 | 8.0 | 24200 | 0.0000 | 1.0 |
| 0.0 | 9.0 | 27225 | 0.0000 | 1.0 |
| 0.0 | 10.0 | 30250 | 0.0000 | 1.0 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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