metadata
license: apache-2.0
base_model: motheecreator/wav2vec2-base-finetuned-ks
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9982174688057041
wav2vec2-base-finetuned-ks
This model is a fine-tuned version of motheecreator/wav2vec2-base-finetuned-ks on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0117
- Accuracy: 0.9982
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0528 | 0.99 | 79 | 0.0318 | 0.9947 |
| 0.0246 | 1.99 | 159 | 0.0132 | 0.9978 |
| 0.0142 | 3.0 | 239 | 0.0158 | 0.9978 |
| 0.007 | 4.0 | 319 | 0.0117 | 0.9982 |
| 0.0004 | 4.95 | 395 | 0.0147 | 0.9982 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2