README.md

metadata

license: apache-2.0
base_model: facebook/hubert-large-ll60k
tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - superb
metrics:
  - accuracy
model-index:
  - name: superb_ks_42
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: superb
          type: superb
          config: ks
          split: validation
          args: ks
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6209179170344219

superb_ks_42

This model is a fine-tuned version of facebook/hubert-large-ll60k on the superb dataset. It achieves the following results on the evaluation set:

• Loss: -7.5697
• Accuracy: 0.6209
• Test Accuracy: 0.6209
• Df Accuracy: 0.1331
• Unlearn Overall Accuracy: 0.7439
• Unlearn Time: 811.1616

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: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Overall Accuracy	Unlearn Overall Accuracy	Time
No log	1.0	96	-7.5697	0.1331	0.7439	0.7439	-1
No log	2.0	192	-16.0056	0.1331	0.7439	0.7439	-1
No log	3.0	288	-25.2304	0.1331	0.7439	0.7439	-1
No log	4.0	384	-35.0470	0.1331	0.7439	0.7439	-1
No log	5.0	480	-44.8008	0.1331	0.7439	0.7439	-1
No log	6.0	576	-53.8368	0.1331	0.7439	0.7439	-1
No log	7.0	672	-61.5362	0.1331	0.7439	0.7439	-1
No log	8.0	768	-67.4056	0.1331	0.7439	0.7439	-1
No log	9.0	864	-71.0815	0.1331	0.7439	0.7439	-1
No log	10.0	960	-72.3418	0.1331	0.7439	0.7439	-1

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2+cu118
• Datasets 2.18.0
• Tokenizers 0.15.2