metadata
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- acordes_completo
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-chorddetection
results: []
distilhubert-finetuned-chorddetection
This model is a fine-tuned version of ntu-spml/distilhubert on the ChordStimation 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 |
|---|---|---|---|---|
| 0.0 | 1.0 | 3025 | 0.0000 | 1.0 |
| 0.0 | 2.0 | 6050 | 0.0000 | 1.0 |
| 0.0 | 3.0 | 9075 | 0.0000 | 1.0 |
| 0.0 | 4.0 | 12100 | 0.0000 | 1.0 |
| 0.0 | 5.0 | 15125 | 0.0000 | 1.0 |
| 0.0 | 6.0 | 18150 | 0.0000 | 1.0 |
| 0.0 | 7.0 | 21175 | 0.0000 | 1.0 |
| 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