update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,90 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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-music-classification
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
name: Audio Classification
|
| 14 |
+
type: audio-classification
|
| 15 |
+
dataset:
|
| 16 |
+
name: GTZAN
|
| 17 |
+
type: marsyas/gtzan
|
| 18 |
+
config: all
|
| 19 |
+
split: train
|
| 20 |
+
args: all
|
| 21 |
+
metrics:
|
| 22 |
+
- name: Accuracy
|
| 23 |
+
type: accuracy
|
| 24 |
+
value: 0.86
|
| 25 |
+
---
|
| 26 |
+
|
| 27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 28 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 29 |
+
|
| 30 |
+
# distilhubert-music-classification
|
| 31 |
+
|
| 32 |
+
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
|
| 33 |
+
It achieves the following results on the evaluation set:
|
| 34 |
+
- Loss: 0.7110
|
| 35 |
+
- Accuracy: 0.86
|
| 36 |
+
|
| 37 |
+
## Model description
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Intended uses & limitations
|
| 42 |
+
|
| 43 |
+
More information needed
|
| 44 |
+
|
| 45 |
+
## Training and evaluation data
|
| 46 |
+
|
| 47 |
+
More information needed
|
| 48 |
+
|
| 49 |
+
## Training procedure
|
| 50 |
+
|
| 51 |
+
### Training hyperparameters
|
| 52 |
+
|
| 53 |
+
The following hyperparameters were used during training:
|
| 54 |
+
- learning_rate: 5e-05
|
| 55 |
+
- train_batch_size: 8
|
| 56 |
+
- eval_batch_size: 8
|
| 57 |
+
- seed: 42
|
| 58 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 59 |
+
- lr_scheduler_type: linear
|
| 60 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 61 |
+
- num_epochs: 16
|
| 62 |
+
|
| 63 |
+
### Training results
|
| 64 |
+
|
| 65 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 66 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
| 67 |
+
| 2.1284 | 1.0 | 113 | 1.9802 | 0.5 |
|
| 68 |
+
| 1.435 | 2.0 | 226 | 1.3403 | 0.65 |
|
| 69 |
+
| 1.0235 | 3.0 | 339 | 0.9941 | 0.74 |
|
| 70 |
+
| 0.8973 | 4.0 | 452 | 0.9184 | 0.69 |
|
| 71 |
+
| 0.7312 | 5.0 | 565 | 0.6918 | 0.79 |
|
| 72 |
+
| 0.4306 | 6.0 | 678 | 0.6343 | 0.78 |
|
| 73 |
+
| 0.4204 | 7.0 | 791 | 0.6174 | 0.83 |
|
| 74 |
+
| 0.1326 | 8.0 | 904 | 0.5888 | 0.83 |
|
| 75 |
+
| 0.0766 | 9.0 | 1017 | 0.5939 | 0.84 |
|
| 76 |
+
| 0.0308 | 10.0 | 1130 | 0.7191 | 0.86 |
|
| 77 |
+
| 0.0318 | 11.0 | 1243 | 0.7308 | 0.84 |
|
| 78 |
+
| 0.0657 | 12.0 | 1356 | 0.7222 | 0.81 |
|
| 79 |
+
| 0.0096 | 13.0 | 1469 | 0.7075 | 0.84 |
|
| 80 |
+
| 0.0077 | 14.0 | 1582 | 0.7268 | 0.84 |
|
| 81 |
+
| 0.0073 | 15.0 | 1695 | 0.6957 | 0.85 |
|
| 82 |
+
| 0.0066 | 16.0 | 1808 | 0.7110 | 0.86 |
|
| 83 |
+
|
| 84 |
+
|
| 85 |
+
### Framework versions
|
| 86 |
+
|
| 87 |
+
- Transformers 4.31.0.dev0
|
| 88 |
+
- Pytorch 2.0.0
|
| 89 |
+
- Datasets 2.1.0
|
| 90 |
+
- Tokenizers 0.13.3
|