update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,78 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- marsyas/gtzan
|
| 7 |
+
metrics:
|
| 8 |
+
- accuracy
|
| 9 |
+
model-index:
|
| 10 |
+
- name: distilhubert-finetuned-gtzan
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# distilhubert-finetuned-gtzan
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.7713
|
| 22 |
+
- Accuracy: 0.87
|
| 23 |
+
|
| 24 |
+
## Model description
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Intended uses & limitations
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training and evaluation data
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training procedure
|
| 37 |
+
|
| 38 |
+
### Training hyperparameters
|
| 39 |
+
|
| 40 |
+
The following hyperparameters were used during training:
|
| 41 |
+
- learning_rate: 0.0001
|
| 42 |
+
- train_batch_size: 8
|
| 43 |
+
- eval_batch_size: 8
|
| 44 |
+
- seed: 42
|
| 45 |
+
- gradient_accumulation_steps: 2
|
| 46 |
+
- total_train_batch_size: 16
|
| 47 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 48 |
+
- lr_scheduler_type: linear
|
| 49 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 50 |
+
- num_epochs: 15
|
| 51 |
+
|
| 52 |
+
### Training results
|
| 53 |
+
|
| 54 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 55 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 56 |
+
| 1.9891 | 0.99 | 56 | 1.9587 | 0.4 |
|
| 57 |
+
| 1.5271 | 2.0 | 113 | 1.4658 | 0.56 |
|
| 58 |
+
| 1.074 | 2.99 | 169 | 0.9198 | 0.79 |
|
| 59 |
+
| 0.8036 | 4.0 | 226 | 0.9191 | 0.7 |
|
| 60 |
+
| 0.5017 | 4.99 | 282 | 0.7299 | 0.8 |
|
| 61 |
+
| 0.3405 | 6.0 | 339 | 0.6682 | 0.8 |
|
| 62 |
+
| 0.2178 | 6.99 | 395 | 0.6877 | 0.82 |
|
| 63 |
+
| 0.116 | 8.0 | 452 | 0.6092 | 0.83 |
|
| 64 |
+
| 0.0616 | 8.99 | 508 | 0.6579 | 0.85 |
|
| 65 |
+
| 0.0229 | 10.0 | 565 | 0.8793 | 0.8 |
|
| 66 |
+
| 0.0128 | 10.99 | 621 | 0.6722 | 0.87 |
|
| 67 |
+
| 0.0094 | 12.0 | 678 | 0.7586 | 0.87 |
|
| 68 |
+
| 0.0073 | 12.99 | 734 | 0.7636 | 0.87 |
|
| 69 |
+
| 0.007 | 14.0 | 791 | 0.7728 | 0.87 |
|
| 70 |
+
| 0.0073 | 14.87 | 840 | 0.7713 | 0.87 |
|
| 71 |
+
|
| 72 |
+
|
| 73 |
+
### Framework versions
|
| 74 |
+
|
| 75 |
+
- Transformers 4.30.2
|
| 76 |
+
- Pytorch 1.11.0+cu102
|
| 77 |
+
- Datasets 2.4.0
|
| 78 |
+
- Tokenizers 0.12.1
|