gokuls / wav2vec2-base-960h-speech-commands

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Total runs: 43
24-hour runs: 0
7-day runs: 30
30-day runs: 36
Model's Last Updated: October 01 2024

Introduction of wav2vec2-base-960h-speech-commands

Model Details of wav2vec2-base-960h-speech-commands

wav2vec2-base-960h-speech-commands

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the speech_commands dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1612
  • Accuracy: 0.8067
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: 48
  • eval_batch_size: 48
  • 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: 20
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Accuracy
1.745 1.0 824 1.9237 0.7648
0.5664 2.0 1648 1.1424 0.7878
0.4337 3.0 2472 1.1234 0.8013
0.3346 4.0 3296 1.1040 0.8035
0.2683 5.0 4120 1.3128 0.7905
0.3498 6.0 4944 1.2172 0.7972
0.2556 7.0 5768 1.1906 0.7986
0.226 8.0 6592 1.1081 0.8044
0.2317 9.0 7416 1.1068 0.8049
0.1144 10.0 8240 1.1612 0.8067
0.2143 11.0 9064 1.1577 0.8031
0.1668 12.0 9888 1.1343 0.8058
0.2504 13.0 10712 1.0583 0.8067
0.218 14.0 11536 1.0677 0.8026
0.1025 15.0 12360 1.0690 0.8053
Framework versions
  • Transformers 4.43.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1

Runs of gokuls wav2vec2-base-960h-speech-commands on huggingface.co

43
Total runs
0
24-hour runs
15
3-day runs
30
7-day runs
36
30-day runs

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wav2vec2-base-960h-speech-commands is an open source model from GitHub that offers a free installation service, and any user can find wav2vec2-base-960h-speech-commands on GitHub to install. At the same time, huggingface.co provides the effect of wav2vec2-base-960h-speech-commands install, users can directly use wav2vec2-base-960h-speech-commands installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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