metadata
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: wav2vec2-base-ks-linear_lrX1000
results: []
wav2vec2-base-ks-linear_lrX1000
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: 0.5661
- Accuracy: 0.8325
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: 0.03
- train_batch_size: 256
- eval_batch_size: 256
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7558 | 1.0 | 50 | 1.0584 | 0.6462 |
| 0.5971 | 2.0 | 100 | 0.7816 | 0.7510 |
| 0.5382 | 3.0 | 150 | 0.7870 | 0.7520 |
| 0.5045 | 4.0 | 200 | 0.6647 | 0.7880 |
| 0.4717 | 5.0 | 250 | 1.1572 | 0.6053 |
| 0.4651 | 6.0 | 300 | 0.6387 | 0.7945 |
| 0.4205 | 7.0 | 350 | 0.5661 | 0.8325 |
| 0.4423 | 8.0 | 400 | 0.7100 | 0.7846 |
| 0.426 | 9.0 | 450 | 0.7054 | 0.7829 |
| 0.4067 | 10.0 | 500 | 0.6288 | 0.8114 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.11.0+cu115
- Datasets 2.4.0
- Tokenizers 0.12.1