metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-conformer-rel-pos-large-finetuned-speech-commands
results:
- task:
type: audio-classification
name: audio classification
dataset:
type: speech_commands
name: speech_commands
split: v0.02
metrics:
- type: accuracy
value: 0.9724
name: accuracy
wav2vec2-conformer-rel-pos-large-finetuned-speech-commands
This model is a fine-tuned version of facebook/wav2vec2-conformer-rel-pos-large on the speech_commands dataset. It achieves the following results on the evaluation set:
- Loss: 0.5245
- Accuracy: 0.9724
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: 256
- eval_batch_size: 256
- seed: 42
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2901 | 1.0 | 83 | 2.0542 | 0.8875 |
| 1.8375 | 2.0 | 166 | 1.5610 | 0.9316 |
| 1.4957 | 3.0 | 249 | 1.1850 | 0.9558 |
| 1.1917 | 4.0 | 332 | 0.9159 | 0.9695 |
| 1.0449 | 5.0 | 415 | 0.7624 | 0.9687 |
| 0.9319 | 6.0 | 498 | 0.6444 | 0.9715 |
| 0.8559 | 7.0 | 581 | 0.5806 | 0.9711 |
| 0.8199 | 8.0 | 664 | 0.5394 | 0.9721 |
| 0.7949 | 9.0 | 747 | 0.5245 | 0.9724 |
| 0.7975 | 10.0 | 830 | 0.5256 | 0.9721 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1