metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- f1
model-index:
- name: wav2vec2-base-finetuned-ks
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: Data_Train
split: train
args: Data_Train
metrics:
- name: F1
type: f1
value: 0.8016517743184772
wav2vec2-base-finetuned-ks
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1858
- F1: 0.8017
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 | F1 |
|---|---|---|---|---|
| 2.6077 | 1.0 | 602 | 2.5802 | 0.1587 |
| 1.9999 | 2.0 | 1204 | 2.0069 | 0.3600 |
| 1.4107 | 3.0 | 1806 | 1.6226 | 0.5527 |
| 0.9977 | 4.0 | 2408 | 1.2932 | 0.6719 |
| 0.8132 | 5.0 | 3010 | 1.2297 | 0.7030 |
| 0.5315 | 6.0 | 3612 | 1.0131 | 0.7745 |
| 0.5772 | 7.0 | 4214 | 1.1444 | 0.7782 |
| 0.0248 | 8.0 | 4816 | 1.1777 | 0.7850 |
| 0.0186 | 9.0 | 5418 | 1.2235 | 0.7910 |
| 0.2457 | 10.0 | 6020 | 1.1858 | 0.8017 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3