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shiv6146
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whisper-large-v2-mn

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Mongolian
whisper
whisper-event
hf-asr-leaderboard
generated_from_multiple_datasets
Eval Results
Inference Endpoints
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whisper-large-v2-mn-13

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1689
  • Wer: 20.0240
  • Cer: 6.6010

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 25000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Cer Validation Loss Wer
0.3921 0.09 1000 15.7845 0.4101 46.9030
0.3115 0.17 2000 14.2911 0.3353 41.8451
0.2659 0.26 3000 11.8131 0.2800 34.6406
0.2477 0.35 4000 10.6659 0.2578 32.0024
0.2274 0.43 5000 10.0460 0.2463 30.3419
0.2059 0.52 6000 9.9264 0.2305 28.5558
0.2092 0.61 7000 9.4277 0.2196 27.8785
0.1956 0.69 8000 9.2745 0.2093 26.8353
0.195 0.78 9000 8.9485 0.2042 26.6168
0.195 0.87 10000 8.5324 0.2001 25.6718
0.1795 0.95 11000 8.1786 0.1936 24.1698
0.1575 1.04 12000 7.8653 0.1915 23.8912
0.1358 1.13 13000 7.6749 0.1918 23.3778
0.1509 1.21 14000 7.7221 0.1852 23.1811
0.1474 1.3 15000 7.3246 0.1764 22.4984
0.1461 1.39 16000 7.3187 0.1793 22.4110
0.134 1.47 17000 7.1123 0.1737 21.9412
0.1289 1.56 18000 7.4593 0.1727 22.0614
0.1287 1.65 19000 7.0230 0.1701 21.4223
0.1196 1.73 20000 6.9447 0.1666 21.2475
0.1275 1.82 21000 6.7956 0.1653 20.8106
0.1329 1.91 22000 6.7729 0.1622 20.3354
0.1294 1.99 23000 6.6448 0.1606 20.2207
0.1043 2.08 24000 6.6010 0.1689 20.0240
0.079 2.17 25000 6.6246 0.1687 20.1005

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2
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Automatic Speech Recognition
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Datasets used to train shiv6146/whisper-large-v2-mn

Evaluation results

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