README.md

metadata

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - minds14
metrics:
  - accuracy
model-index:
  - name: test_audio_classification
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: minds14
          type: minds14
          config: en-US
          split: train
          args: en-US
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.035398230088495575

test_audio_classification

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Accuracy: 0.0354

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• 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
No log	0.8	3	nan	0.0354
No log	1.87	7	nan	0.0354
95.5104	2.93	11	nan	0.0354
95.5104	4.0	15	nan	0.0354
95.5104	4.8	18	nan	0.0354
0.0	5.87	22	nan	0.0354
0.0	6.93	26	nan	0.0354
0.0	8.0	30	nan	0.0354

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2