abdouaziiz's picture
Upload 6 files
ffc6710
|
raw
history blame
2.47 kB
metadata
tags:
  - audio-classification
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - f1
model-index:
  - name: wavlm-base
    results: []

wavlm-base

This model is a fine-tuned version of microsoft/wavlm-base on the galsenai/waxal_dataset dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1345
  • Accuracy: 0.6783
  • Precision: 0.8774
  • F1: 0.7615

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: 30
  • eval_batch_size: 30
  • seed: 0
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 120
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 32.0

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision F1
4.4506 2.53 500 4.8601 0.0224 0.0136 0.0066
3.0523 5.05 1000 4.6674 0.0720 0.0460 0.0394
1.949 7.58 1500 4.1533 0.1156 0.1847 0.1064
1.3427 10.1 2000 3.8173 0.1448 0.2382 0.1347
1.0064 12.63 2500 3.5546 0.2183 0.4464 0.2385
0.7985 15.15 3000 3.1172 0.3842 0.6336 0.4258
0.6505 17.68 3500 2.9231 0.5165 0.7677 0.5995
0.5367 20.2 4000 2.4935 0.5961 0.8182 0.6755
0.465 22.73 4500 2.2411 0.6412 0.8624 0.7272
0.4075 25.25 5000 2.1345 0.6783 0.8774 0.7615
0.3793 27.78 5500 2.2535 0.6681 0.8792 0.7543
0.3418 30.3 6000 2.3390 0.6662 0.8905 0.7576

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.11.0+cu113
  • Datasets 2.9.1.dev0
  • Tokenizers 0.13.2