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Moroccan-Darija-STT-large-v1.6.10

Automatic Speech Recognition
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whisper
Generated from Trainer
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Moroccan-Darija-STT-large-v1.6.10 / README.md
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BounharAbdelaziz/Moroccan-Darija-STT-large-v1.6.10
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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Moroccan-Darija-STT-large-v1.6.10
    results: []

Moroccan-Darija-STT-large-v1.6.10

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5413
  • Wer: 78.1961
  • Cer: 38.0589

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.8531 0.1473 30 0.3501 188.0940 155.4803
0.666 0.2947 60 0.3092 104.0495 61.4107
0.578 0.4420 90 0.3034 79.7356 38.7565
0.5255 0.5893 120 0.3006 77.0164 35.8951
0.4326 0.7366 150 0.3038 75.2175 32.5845
0.4941 0.8840 180 0.3091 71.1094 29.9579
0.3748 1.0344 210 0.3131 79.5766 39.2294
0.3613 1.1817 240 0.3339 72.2557 31.5373
0.3328 1.3290 270 0.3273 70.8835 30.4174
0.3032 1.4764 300 0.3430 69.4863 29.2451
0.2933 1.6237 330 0.3484 74.7406 34.7466
0.2593 1.7710 360 0.3523 75.3263 34.0287
0.2487 1.9184 390 0.3500 83.5843 41.7783
0.1815 2.0688 420 0.3783 81.2249 40.5233
0.1648 2.2161 450 0.3847 78.9324 38.8409
0.1533 2.3634 480 0.3979 78.7149 37.9981
0.1358 2.5107 510 0.4050 77.1670 36.0556
0.1261 2.6581 540 0.4099 80.7982 41.2479
0.1274 2.8054 570 0.4234 81.8106 41.7834
0.1141 2.9527 600 0.4223 79.1499 38.9389
0.0713 3.1031 630 0.4516 93.3233 52.0920
0.0624 3.2505 660 0.4555 81.7185 40.3071
0.066 3.3978 690 0.4652 82.4799 42.5181
0.063 3.5451 720 0.4673 79.5850 39.5909
0.059 3.6924 750 0.4690 86.5462 46.5010
0.0519 3.8398 780 0.4795 86.8725 47.4554
0.0514 3.9871 810 0.4876 86.3286 45.5213
0.0367 4.1375 840 0.5028 83.6931 43.3796
0.0353 4.2848 870 0.5070 80.6225 40.6888
0.0367 4.4322 900 0.5084 78.1961 38.5470
0.0309 4.5795 930 0.5146 79.6854 39.2396
0.0328 4.7268 960 0.5134 78.2965 39.1517
0.0314 4.8742 990 0.5284 78.4137 38.3274
0.0257 5.0246 1020 0.5273 76.3554 37.1214
0.0229 5.1719 1050 0.5342 84.5298 43.8677
0.0245 5.3192 1080 0.5354 82.0783 42.5080
0.0203 5.4665 1110 0.5407 86.2533 46.4622
0.0237 5.6139 1140 0.5427 81.3922 40.7547
0.021 5.7612 1170 0.5413 77.2005 37.2566
0.0229 5.9085 1200 0.5413 78.1961 38.0589

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.21.0