Anujgr8 / wav2vec2-base-Tamil-large

huggingface.co
Total runs: 1.7K
24-hour runs: 0
7-day runs: -4.6K
30-day runs: -3.0K
Model's Last Updated: June 15 2024
automatic-speech-recognition

Introduction of wav2vec2-base-Tamil-large

Model Details of wav2vec2-base-Tamil-large

wav2vec2-base-Tamil-large

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3015
  • Wer: 0.3470
  • Cer: 0.0610
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: 0.0003
  • train_batch_size: 6
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 24
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 3000
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer Cer
5.2014 2.2472 300 3.2558 1.0 1.0
1.1765 4.4944 600 0.5245 0.7139 0.1482
0.4765 6.7416 900 0.4191 0.6080 0.1133
0.33 8.9888 1200 0.3494 0.4983 0.0910
0.2488 11.2360 1500 0.3163 0.4470 0.0811
0.1951 13.4831 1800 0.3326 0.4179 0.0748
0.1586 15.7303 2100 0.3135 0.3924 0.0702
0.1308 17.9775 2400 0.3070 0.3798 0.0668
0.1111 20.2247 2700 0.2999 0.3618 0.0635
0.0996 22.4719 3000 0.3015 0.3470 0.0610
Framework versions
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 1.18.3
  • Tokenizers 0.19.1

Runs of Anujgr8 wav2vec2-base-Tamil-large on huggingface.co

1.7K
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0
24-hour runs
-4.7K
3-day runs
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7-day runs
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30-day runs

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