metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: vivos
type: vivos
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.0013157894736842105
wav2vec2-base-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the vivos dataset. It achieves the following results on the evaluation set:
- Loss: 5.3540
- Accuracy: 0.0013
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7037 | 0.9997 | 1457 | 5.3540 | 0.0013 |
| 0.0203 | 2.0 | 2915 | 8.2572 | 0.0013 |
| 0.0718 | 2.9997 | 4372 | 9.1738 | 0.0 |
| 0.0027 | 4.0 | 5830 | 10.0341 | 0.0 |
| 0.0019 | 4.9983 | 7285 | 10.3670 | 0.0 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.19.1