metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: intent_classify
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: minds14
type: minds14
config: en-US
split: train
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.02654867256637168
intent_classify
This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 2.6794
- Accuracy: 0.0265
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 2.6388 | 0.98 | 14 | 2.6441 | 0.0619 |
| 2.6348 | 1.96 | 28 | 2.6521 | 0.0973 |
| 2.6138 | 2.95 | 42 | 2.6635 | 0.0708 |
| 2.6282 | 4.0 | 57 | 2.6674 | 0.0708 |
| 2.6106 | 4.98 | 71 | 2.6727 | 0.0531 |
| 2.6046 | 5.96 | 85 | 2.6719 | 0.0531 |
| 2.5935 | 6.95 | 99 | 2.6757 | 0.0442 |
| 2.5884 | 8.0 | 114 | 2.6778 | 0.0265 |
| 2.5791 | 8.98 | 128 | 2.6785 | 0.0265 |
| 2.5789 | 9.82 | 140 | 2.6794 | 0.0265 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.2