Anujgr8 / w2v-bert-Tamil-large

huggingface.co
Total runs: 6
24-hour runs: -1
7-day runs: 2
30-day runs: 3
Model's Last Updated: June 16 2024
automatic-speech-recognition

Introduction of w2v-bert-Tamil-large

Model Details of w2v-bert-Tamil-large

w2v-bert-Tamil-large

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1815
  • Wer: 0.2176
  • Cer: 0.0328
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: 2
  • eval_batch_size: 8
  • 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_steps: 500
  • training_steps: 3000
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer Cer
2.0779 0.75 300 0.4934 0.6338 0.1189
0.3653 1.5 600 0.4045 0.5424 0.0975
0.2632 2.25 900 0.3148 0.4421 0.0723
0.2084 3.0 1200 0.2297 0.3499 0.0576
0.1359 3.75 1500 0.2042 0.3060 0.0464
0.1049 4.5 1800 0.1939 0.2836 0.0446
0.0823 5.25 2100 0.1827 0.2504 0.0382
0.0561 6.0 2400 0.1731 0.2419 0.0368
0.0352 6.75 2700 0.1802 0.2275 0.0335
0.0224 7.5 3000 0.1815 0.2176 0.0328
Framework versions
  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1

Runs of Anujgr8 w2v-bert-Tamil-large on huggingface.co

6
Total runs
-1
24-hour runs
-1
3-day runs
2
7-day runs
3
30-day runs

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