metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: wav2vec2-large-xlsr-53-english-pronunciation-evaluation-aod-cut-balance
    results: []

wav2vec2-large-xlsr-53-english-pronunciation-evaluation-aod-cut-balance

This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-english on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0674
Accuracy: 0.6055
F1: 0.6017
Precision: 0.6074
Recall: 0.6055

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: 8
eval_batch_size: 8
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0011	1.0	105	1.0494	0.5	0.4111	0.4721	0.5
0.7777	2.0	210	0.9454	0.5576	0.5178	0.5332	0.5576
0.7462	3.0	315	1.1190	0.5815	0.5649	0.5757	0.5815
0.6099	4.0	420	1.0299	0.6043	0.5975	0.5992	0.6043
0.4457	5.0	525	1.0674	0.6055	0.6017	0.6074	0.6055

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3