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makhataei
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Whisper-Small-Common-Voice

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Persian
whisper
fa-asr
Generated from Trainer
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End of training

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  1. README.md +46 -16
  2. model.safetensors +1 -1
  3. runs/Mar12_13-32-10_Software-AI/events.out.tfevents.1710237731.Software-AI.1071185.0 +2 -2
README.md CHANGED
@@ -20,8 +20,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [makhataei/Whisper-Small-Common-Voice](https://huggingface.co/makhataei/Whisper-Small-Common-Voice) on the Ctejarat dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5782
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- - Wer: 36.9283
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  ## Model description
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@@ -48,23 +48,53 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 80
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 5
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- - training_steps: 100
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|
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- | 0.904 | 0.96 | 10 | 0.8973 | 46.7577 |
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- | 0.7728 | 1.93 | 20 | 0.7814 | 42.3208 |
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- | 0.6586 | 2.89 | 30 | 0.7098 | 40.3413 |
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- | 0.586 | 3.86 | 40 | 0.6623 | 39.5904 |
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- | 0.5336 | 4.82 | 50 | 0.6310 | 38.9078 |
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- | 0.512 | 5.78 | 60 | 0.6091 | 37.6792 |
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- | 0.4732 | 6.75 | 70 | 0.5945 | 37.6792 |
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- | 0.4367 | 7.71 | 80 | 0.5851 | 37.2696 |
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- | 0.4282 | 8.67 | 90 | 0.5800 | 37.0648 |
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- | 0.4398 | 9.64 | 100 | 0.5782 | 36.9283 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [makhataei/Whisper-Small-Common-Voice](https://huggingface.co/makhataei/Whisper-Small-Common-Voice) on the Ctejarat dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5349
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+ - Wer: 26.2116
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  ## Model description
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  - total_train_batch_size: 80
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - training_steps: 4000
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.2944 | 9.64 | 100 | 0.4843 | 33.6519 |
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+ | 0.1048 | 19.28 | 200 | 0.4394 | 30.1706 |
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+ | 0.0273 | 28.92 | 300 | 0.4493 | 29.7611 |
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+ | 0.0083 | 38.55 | 400 | 0.4645 | 29.4198 |
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+ | 0.0042 | 48.19 | 500 | 0.4744 | 28.5324 |
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+ | 0.0026 | 57.83 | 600 | 0.4811 | 28.3276 |
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+ | 0.0018 | 67.47 | 700 | 0.4863 | 27.6451 |
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+ | 0.0014 | 77.11 | 800 | 0.4907 | 27.7816 |
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+ | 0.0012 | 86.75 | 900 | 0.4945 | 27.4403 |
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+ | 0.0009 | 96.39 | 1000 | 0.4979 | 27.4403 |
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+ | 0.0008 | 106.02 | 1100 | 0.5010 | 26.8259 |
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+ | 0.0007 | 115.66 | 1200 | 0.5036 | 26.8259 |
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+ | 0.0006 | 125.3 | 1300 | 0.5062 | 26.6894 |
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+ | 0.0006 | 134.94 | 1400 | 0.5085 | 26.3481 |
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+ | 0.0005 | 144.58 | 1500 | 0.5107 | 26.3481 |
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+ | 0.0004 | 154.22 | 1600 | 0.5126 | 26.4164 |
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+ | 0.0004 | 163.86 | 1700 | 0.5145 | 26.4846 |
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+ | 0.0004 | 173.49 | 1800 | 0.5163 | 26.3481 |
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+ | 0.0003 | 183.13 | 1900 | 0.5179 | 30.8532 |
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+ | 0.0003 | 192.77 | 2000 | 0.5194 | 30.8532 |
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+ | 0.0003 | 202.41 | 2100 | 0.5209 | 30.7850 |
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+ | 0.0003 | 212.05 | 2200 | 0.5222 | 30.9215 |
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+ | 0.0003 | 221.69 | 2300 | 0.5236 | 30.9215 |
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+ | 0.0003 | 231.33 | 2400 | 0.5248 | 30.9215 |
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+ | 0.0002 | 240.96 | 2500 | 0.5259 | 30.9215 |
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+ | 0.0002 | 250.6 | 2600 | 0.5270 | 30.7167 |
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+ | 0.0002 | 260.24 | 2700 | 0.5280 | 30.8532 |
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+ | 0.0002 | 269.88 | 2800 | 0.5290 | 30.8532 |
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+ | 0.0002 | 279.52 | 2900 | 0.5299 | 30.7167 |
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+ | 0.0002 | 289.16 | 3000 | 0.5306 | 30.7167 |
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+ | 0.0002 | 298.8 | 3100 | 0.5314 | 30.7167 |
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+ | 0.0002 | 308.43 | 3200 | 0.5321 | 30.7167 |
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+ | 0.0002 | 318.07 | 3300 | 0.5327 | 30.7850 |
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+ | 0.0002 | 327.71 | 3400 | 0.5333 | 30.7167 |
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+ | 0.0002 | 337.35 | 3500 | 0.5337 | 30.7167 |
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+ | 0.0002 | 346.99 | 3600 | 0.5341 | 30.7167 |
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+ | 0.0002 | 356.63 | 3700 | 0.5344 | 30.6485 |
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+ | 0.0002 | 366.27 | 3800 | 0.5347 | 26.2116 |
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+ | 0.0002 | 375.9 | 3900 | 0.5348 | 26.2116 |
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+ | 0.0002 | 385.54 | 4000 | 0.5349 | 26.2116 |
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  ### Framework versions
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