metadata

license: apache-2.0
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - common_language
metrics:
  - accuracy
model-index:
  - name: hubert-base-common-language
    results: []

hubert-base-common-language

This model is a fine-tuned version of facebook/hubert-base-ls960 on the common_language dataset. It achieves the following results on the evaluation set:

Loss: 1.3477
Accuracy: 0.7317

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: 1
eval_batch_size: 4
seed: 0
distributed_type: IPU
gradient_accumulation_steps: 32
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.25
num_epochs: 10.0
training precision: Mixed Precision

Training results

Framework versions

Transformers 4.18.0.dev0
Pytorch 1.10.0+cpu
Datasets 2.0.0
Tokenizers 0.11.6