metadata
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-speech-commands-h
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: speech_commands
type: speech_commands
config: v0.02
split: None
args: v0.02
metrics:
- name: Accuracy
type: accuracy
value: 0
wav2vec2-base-960h-speech-commands-h
This model is a fine-tuned version of facebook/wav2vec2-base-960h on the speech_commands dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.0
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: 48
- eval_batch_size: 48
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0 | 1.0 | 824 | nan | 0.0 |
| 0.0 | 2.0 | 1648 | nan | 0.0 |
| 0.0 | 3.0 | 2472 | nan | 0.0 |
| 0.0 | 4.0 | 3296 | nan | 0.0 |
| 0.0 | 5.0 | 4120 | nan | 0.0 |
| 0.0 | 6.0 | 4944 | nan | 0.0 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1