|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hubert-large-ls960-ft-finetuned-gtzan |
|
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. --> |
|
|
|
# hubert-large-ls960-ft-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: nan |
|
- Accuracy: 0.8 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.2564 | 1.0 | 112 | 2.2597 | 0.37 | |
|
| 1.6529 | 2.0 | 225 | 1.8087 | 0.27 | |
|
| 1.4922 | 3.0 | 337 | 1.4067 | 0.48 | |
|
| 1.3749 | 4.0 | 450 | 1.3045 | 0.55 | |
|
| 0.9226 | 5.0 | 562 | 1.1160 | 0.64 | |
|
| 0.8591 | 6.0 | 675 | 0.8981 | 0.69 | |
|
| 0.5988 | 7.0 | 787 | 0.9898 | 0.71 | |
|
| 1.0143 | 8.0 | 900 | 1.0200 | 0.69 | |
|
| 0.464 | 9.0 | 1012 | 0.5678 | 0.82 | |
|
| 0.6969 | 10.0 | 1125 | 0.7087 | 0.81 | |
|
| 0.5547 | 11.0 | 1237 | 0.7278 | 0.75 | |
|
| 0.2638 | 12.0 | 1350 | 0.7599 | 0.8 | |
|
| 0.3504 | 13.0 | 1462 | 0.6778 | 0.85 | |
|
| 0.106 | 14.0 | 1575 | 0.7504 | 0.82 | |
|
| 0.3392 | 15.0 | 1687 | 0.7514 | 0.84 | |
|
| 0.1516 | 16.0 | 1800 | 0.8678 | 0.8 | |
|
| 0.1324 | 17.0 | 1912 | 0.7644 | 0.84 | |
|
| 0.0827 | 18.0 | 2025 | nan | 0.8 | |
|
| 0.45 | 19.0 | 2137 | nan | 0.8 | |
|
| 0.2407 | 19.91 | 2240 | nan | 0.8 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.0.dev0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|