metadata

license: apache-2.0
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - mir_st500
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-mirst500
    results: []

wav2vec2-base-mirst500

This model is a fine-tuned version of facebook/wav2vec2-base on the /workspace/datasets/datasets/MIR_ST500/MIR_ST500_AUDIO_CLASSIFICATION.py dataset. It achieves the following results on the evaluation set:

Loss: 1.1219
Accuracy: 0.5817

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: 1
seed: 0
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 4
total_train_batch_size: 128
total_eval_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1779	1.0	1304	1.1219	0.5817

Framework versions

Transformers 4.15.0
Pytorch 1.9.1+cu102
Datasets 2.0.0
Tokenizers 0.10.3