wav2vec2-fluency-checkpoints – AI Model by Yilin0601 | AlphaNeural AI

You can deploy this model and start earning money today!

Yilin0601/
wav2vec2-fluency-checkpoints

like

0

audio-classification

generated_from_trainer

facebook/wav2vec2-base-960h

endpoints_compatible

Views

No views yet

wav2vec2-fluency-checkpoints

This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.6840
Accuracy: 0.24
F1: 0.0484
Qwk: 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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Qwk
1.9027	1.0	149	1.5752	0.3919	0.0804	0.0
1.5771	2.0	298	1.5067	0.3919	0.0804	0.0
1.8437	3.0	447	1.5069	0.3919	0.0804	0.0
1.5636	4.0	596	1.5043	0.3919	0.0804	0.0
1.7911	5.0	745	1.5095	0.3919	0.0804	0.0

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1