|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- superb |
|
metrics: |
|
- accuracy |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: wav2vec2-base-finetuned-ks |
|
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: 0.9832303618711385 |
|
- name: Recall |
|
type: recall |
|
value: 0.9664413018718482 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9719648106690262 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# wav2vec2-base-finetuned-ks |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the superb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0711 |
|
- Accuracy: 0.9832 |
|
- Recall: 0.9664 |
|
- F1: 0.9720 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:| |
|
| 0.4397 | 1.0 | 798 | 0.2810 | 0.9651 | 0.9289 | 0.9361 | |
|
| 0.2067 | 2.0 | 1597 | 0.1142 | 0.9769 | 0.9536 | 0.9593 | |
|
| 0.1881 | 3.0 | 2395 | 0.0829 | 0.9821 | 0.9644 | 0.9693 | |
|
| 0.1167 | 4.0 | 3194 | 0.0752 | 0.9831 | 0.9644 | 0.9726 | |
|
| 0.13 | 5.0 | 3990 | 0.0711 | 0.9832 | 0.9664 | 0.9720 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
