metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_ks_42
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: superb
type: superb
config: ks
split: validation
args: ks
metrics:
- name: Accuracy
type: accuracy
value: 0.6203295086790233
superb_ks_42
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 152.4868
- Accuracy: 0.6203
- Test Accuracy: 0.6203
- Df Accuracy: 0.1343
- Unlearn Overall Accuracy: 0.7430
- Unlearn Time: 743.2490
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 1503 | 69.1496 | 0.1362 | 0.7421 | 0.7421 | -1 |
| 0.0 | 2.0 | 3006 | 141.0801 | 0.1343 | 0.7427 | 0.7427 | -1 |
| 0.0 | 2.5 | 3758 | 152.4868 | 0.1343 | 0.7430 | 0.7430 | -1 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2