model_dialect / README.md
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metadata
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: model_dialect
    results: []

model_dialect

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6309
  • Accuracy: 0.7529
  • Precision: 0.7608
  • Recall: 0.7661
  • F1: 0.7623

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: 5e-05
  • 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
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
1.3499 1.0 217 1.4002 0.4065 0.2570 0.3730 0.2609
1.2635 2.0 434 1.0922 0.5242 0.6868 0.4970 0.4952
1.0379 3.0 651 1.0788 0.5335 0.7047 0.5137 0.5053
0.9536 4.0 868 0.8706 0.6513 0.6804 0.6631 0.6668
0.9321 5.0 1085 0.9052 0.6397 0.6693 0.6474 0.6307
0.9395 6.0 1302 0.8028 0.6767 0.7494 0.6692 0.6845
0.752 7.0 1519 0.7386 0.7344 0.7650 0.7386 0.7441
0.7984 8.0 1736 0.7100 0.7206 0.7370 0.7383 0.7323
0.5841 9.0 1953 0.6509 0.7413 0.7525 0.7494 0.7503
0.6678 10.0 2170 0.6309 0.7529 0.7608 0.7661 0.7623

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0