File size: 1,891 Bytes
1a2ec3a |
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 |
---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- augmented_bass_sounds
metrics:
- accuracy
model-index:
- name: distilhubert-bass9
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: TheDuyx/augmented_bass_sounds
type: augmented_bass_sounds
metrics:
- name: Accuracy
type: accuracy
value: 0.9994121105232217
---
<!-- 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-bass9
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the TheDuyx/augmented_bass_sounds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0024
- Accuracy: 0.9994
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0433 | 1.0 | 382 | 0.0492 | 0.9877 |
| 0.0022 | 2.0 | 765 | 0.0061 | 0.9982 |
| 0.0013 | 2.99 | 1146 | 0.0024 | 0.9994 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2
|