File size: 2,582 Bytes
0a16619 |
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 |
---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8
---
<!-- 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
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: 0.6141
- 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1976 | 0.99 | 56 | 2.1232 | 0.36 |
| 1.5738 | 2.0 | 113 | 1.4564 | 0.68 |
| 1.2321 | 2.99 | 169 | 1.1535 | 0.74 |
| 0.9847 | 4.0 | 226 | 0.9799 | 0.74 |
| 0.8254 | 4.99 | 282 | 0.8700 | 0.78 |
| 0.6017 | 6.0 | 339 | 0.8466 | 0.74 |
| 0.631 | 6.99 | 395 | 0.6828 | 0.8 |
| 0.4887 | 8.0 | 452 | 0.6360 | 0.81 |
| 0.3798 | 8.99 | 508 | 0.6158 | 0.82 |
| 0.2427 | 10.0 | 565 | 0.6163 | 0.78 |
| 0.2077 | 10.99 | 621 | 0.6197 | 0.8 |
| 0.1506 | 12.0 | 678 | 0.5992 | 0.8 |
| 0.1467 | 12.99 | 734 | 0.6003 | 0.8 |
| 0.1967 | 13.88 | 784 | 0.6141 | 0.8 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|