File size: 3,526 Bytes
09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 09fbfc0 c811489 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 |
---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-30-epochs
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.81
---
<!-- 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-gtzan-30-epochs
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1939
- Accuracy: 0.81
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1804 | 1.0 | 113 | 2.1756 | 0.46 |
| 1.7271 | 2.0 | 226 | 1.6973 | 0.53 |
| 1.2703 | 3.0 | 339 | 1.2950 | 0.51 |
| 0.9446 | 4.0 | 452 | 0.9433 | 0.68 |
| 0.6192 | 5.0 | 565 | 0.7885 | 0.73 |
| 0.3628 | 6.0 | 678 | 0.8338 | 0.76 |
| 0.2871 | 7.0 | 791 | 0.8125 | 0.74 |
| 0.0587 | 8.0 | 904 | 0.7500 | 0.8 |
| 0.1316 | 9.0 | 1017 | 0.8711 | 0.79 |
| 0.0175 | 10.0 | 1130 | 0.7429 | 0.82 |
| 0.0818 | 11.0 | 1243 | 0.9848 | 0.81 |
| 0.0049 | 12.0 | 1356 | 1.0498 | 0.76 |
| 0.0034 | 13.0 | 1469 | 1.0422 | 0.84 |
| 0.0028 | 14.0 | 1582 | 1.0919 | 0.83 |
| 0.0023 | 15.0 | 1695 | 1.0565 | 0.82 |
| 0.0019 | 16.0 | 1808 | 1.0797 | 0.84 |
| 0.0769 | 17.0 | 1921 | 1.1430 | 0.82 |
| 0.104 | 18.0 | 2034 | 1.1482 | 0.8 |
| 0.0014 | 19.0 | 2147 | 1.0972 | 0.83 |
| 0.0012 | 20.0 | 2260 | 1.1867 | 0.82 |
| 0.0012 | 21.0 | 2373 | 1.1914 | 0.82 |
| 0.0012 | 22.0 | 2486 | 1.1461 | 0.84 |
| 0.0009 | 23.0 | 2599 | 1.1401 | 0.82 |
| 0.0009 | 24.0 | 2712 | 1.1686 | 0.84 |
| 0.0009 | 25.0 | 2825 | 1.1824 | 0.85 |
| 0.0009 | 26.0 | 2938 | 1.1815 | 0.81 |
| 0.0008 | 27.0 | 3051 | 1.1808 | 0.82 |
| 0.0008 | 28.0 | 3164 | 1.1904 | 0.81 |
| 0.0008 | 29.0 | 3277 | 1.1990 | 0.82 |
| 0.0008 | 30.0 | 3390 | 1.1939 | 0.81 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|