metadata

license: bsd-3-clause
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2
    results: []

ast-finetuned-audioset-10-10-0.4593_ft_env_aug_0-2

This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6899
Accuracy: 0.9643
Precision: 0.9694
Recall: 0.9643
F1: 0.9631

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: 2e-06
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
2.0165	1.0	28	1.6252	0.4643	0.5373	0.4643	0.4711
1.3702	2.0	56	1.0553	0.8571	0.8929	0.8571	0.8536
0.8861	3.0	84	0.6899	0.9643	0.9694	0.9643	0.9631
0.5655	4.0	112	0.4766	0.9643	0.9694	0.9643	0.9631
0.4232	5.0	140	0.3403	0.9643	0.9694	0.9643	0.9631
0.3148	6.0	168	0.2679	0.9643	0.9694	0.9643	0.9631
0.2335	7.0	196	0.2239	0.9643	0.9694	0.9643	0.9631
0.176	8.0	224	0.1979	0.9643	0.9694	0.9643	0.9631
0.1624	9.0	252	0.1824	0.9643	0.9694	0.9643	0.9631
0.1466	10.0	280	0.1781	0.9643	0.9694	0.9643	0.9631

Framework versions

Transformers 4.27.4
Pytorch 2.0.0
Datasets 2.10.1
Tokenizers 0.11.0