metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- precision
model-index:
- name: wav2vec2-base-finetuned-ks
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: Data_Train
split: train
args: Data_Train
metrics:
- name: Precision
type: precision
value: 0.8241279069767442
wav2vec2-base-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0003
- Precision: 0.8241
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision |
|---|---|---|---|---|
| 2.5909 | 1.0 | 688 | 2.4765 | 0.2253 |
| 1.9983 | 2.0 | 1376 | 1.6935 | 0.5262 |
| 1.2894 | 3.0 | 2064 | 1.3080 | 0.6860 |
| 0.9059 | 4.0 | 2752 | 0.9770 | 0.7384 |
| 0.4651 | 5.0 | 3440 | 0.8961 | 0.7762 |
| 0.7273 | 6.0 | 4128 | 0.9682 | 0.7892 |
| 0.366 | 7.0 | 4816 | 1.0405 | 0.7951 |
| 0.8745 | 8.0 | 5504 | 1.0784 | 0.8023 |
| 0.1568 | 9.0 | 6192 | 1.0328 | 0.8169 |
| 0.4805 | 10.0 | 6880 | 1.0003 | 0.8241 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3