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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
Inference Endpoints
Model card Files Metrics Community
makhataei commited on
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End of training

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  1. README.md +104 -104
  2. model.safetensors +1 -1
README.md CHANGED
@@ -2,7 +2,7 @@
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  language:
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  - fa
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  license: apache-2.0
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- base_model: openai/whisper-small
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  tags:
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  - fa-asr
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  - generated_from_trainer
@@ -20,10 +20,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Whisper Small Persian
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- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 15.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9061
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- - Wer: 51.3701
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  ## Model description
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@@ -58,106 +58,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
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- | 0.7495 | 0.39 | 100 | 0.8602 | 58.0774 |
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- | 0.3059 | 0.77 | 200 | 0.5538 | 55.2248 |
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- | 0.2002 | 1.16 | 300 | 0.5137 | 52.4615 |
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- | 0.1798 | 1.54 | 400 | 0.5103 | 51.6578 |
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- | 0.1678 | 1.93 | 500 | 0.4806 | 46.5512 |
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- | 0.0932 | 2.32 | 600 | 0.4936 | 47.4955 |
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- | 0.0944 | 2.7 | 700 | 0.5120 | 48.9160 |
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- | 0.0493 | 3.09 | 800 | 0.5198 | 48.2611 |
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- | 0.0506 | 3.47 | 900 | 0.5227 | 47.4128 |
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- | 0.0482 | 3.86 | 1000 | 0.5256 | 46.9498 |
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- | 0.0244 | 4.25 | 1100 | 0.5491 | 46.0849 |
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- | 0.0272 | 4.63 | 1200 | 0.5621 | 46.9167 |
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- | 0.0246 | 5.02 | 1300 | 0.5856 | 48.8036 |
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- | 0.0159 | 5.41 | 1400 | 0.6145 | 48.3041 |
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- | 0.0152 | 5.79 | 1500 | 0.6178 | 47.7568 |
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- | 0.008 | 6.18 | 1600 | 0.6191 | 48.0611 |
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- | 0.0077 | 6.56 | 1700 | 0.6309 | 46.3594 |
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- | 0.0097 | 6.95 | 1800 | 0.6272 | 47.9139 |
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- | 0.0056 | 7.34 | 1900 | 0.6594 | 46.5562 |
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- | 0.0049 | 7.72 | 2000 | 0.6581 | 47.5831 |
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- | 0.0042 | 8.11 | 2100 | 0.6953 | 48.0925 |
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- | 0.0038 | 8.49 | 2200 | 0.6857 | 48.3719 |
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- | 0.0033 | 8.88 | 2300 | 0.6983 | 49.6965 |
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- | 0.003 | 9.27 | 2400 | 0.7109 | 48.1173 |
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- | 0.0033 | 9.65 | 2500 | 0.6899 | 48.2363 |
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- | 0.0027 | 10.04 | 2600 | 0.7074 | 48.3405 |
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- | 0.0035 | 10.42 | 2700 | 0.7018 | 47.1003 |
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- | 0.0026 | 10.81 | 2800 | 0.7198 | 47.1251 |
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- | 0.0027 | 11.2 | 2900 | 0.7460 | 48.2760 |
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- | 0.0023 | 11.58 | 3000 | 0.7348 | 47.7154 |
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- | 0.0023 | 11.97 | 3100 | 0.7387 | 48.0081 |
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- | 0.0024 | 12.36 | 3200 | 0.7199 | 46.8687 |
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- | 0.0033 | 12.74 | 3300 | 0.7250 | 48.6895 |
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- | 0.0017 | 13.13 | 3400 | 0.7242 | 49.0450 |
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- | 0.0016 | 13.51 | 3500 | 0.7359 | 48.7010 |
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- | 0.0022 | 13.9 | 3600 | 0.7220 | 48.1371 |
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- | 0.0016 | 14.29 | 3700 | 0.7431 | 46.7563 |
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- | 0.0012 | 14.67 | 3800 | 0.7564 | 47.0143 |
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- | 0.0014 | 15.06 | 3900 | 0.7770 | 47.0242 |
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- | 0.0008 | 15.44 | 4000 | 0.8116 | 48.4695 |
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- | 0.0015 | 15.83 | 4100 | 0.7623 | 48.0925 |
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- | 0.002 | 16.22 | 4200 | 0.7699 | 47.7254 |
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- | 0.001 | 16.6 | 4300 | 0.7631 | 46.8754 |
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- | 0.0009 | 16.99 | 4400 | 0.7591 | 48.4166 |
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- | 0.0008 | 17.37 | 4500 | 0.7797 | 47.1780 |
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- | 0.0008 | 17.76 | 4600 | 0.7851 | 46.7662 |
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- | 0.0007 | 18.15 | 4700 | 0.7897 | 48.3157 |
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- | 0.0006 | 18.53 | 4800 | 0.7760 | 48.8069 |
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- | 0.0016 | 18.92 | 4900 | 0.7763 | 47.9718 |
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- | 0.0009 | 19.31 | 5000 | 0.8151 | 48.1586 |
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- | 0.0004 | 19.69 | 5100 | 0.7967 | 47.5567 |
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- | 0.0007 | 20.08 | 5200 | 0.8094 | 46.7861 |
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- | 0.001 | 20.46 | 5300 | 0.8206 | 47.1565 |
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- | 0.0008 | 20.85 | 5400 | 0.8015 | 47.6212 |
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- | 0.0004 | 21.24 | 5500 | 0.8104 | 47.2210 |
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- | 0.0003 | 21.62 | 5600 | 0.8020 | 48.1454 |
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- | 0.0004 | 22.01 | 5700 | 0.8295 | 46.9415 |
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- | 0.0004 | 22.39 | 5800 | 0.8228 | 46.6108 |
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- | 0.0005 | 22.78 | 5900 | 0.8386 | 48.0974 |
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- | 0.0007 | 23.17 | 6000 | 0.8415 | 46.6141 |
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- | 0.0003 | 23.55 | 6100 | 0.8283 | 46.3263 |
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- | 0.0005 | 23.94 | 6200 | 0.8342 | 45.9658 |
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- | 0.0002 | 24.32 | 6300 | 0.8379 | 46.6240 |
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- | 0.0005 | 24.71 | 6400 | 0.8371 | 48.0809 |
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- | 0.0002 | 25.1 | 6500 | 0.8258 | 47.5864 |
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- | 0.0001 | 25.48 | 6600 | 0.8396 | 47.2607 |
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- | 0.0002 | 25.87 | 6700 | 0.8491 | 47.5435 |
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- | 0.0005 | 26.25 | 6800 | 0.8444 | 48.9937 |
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- | 0.0001 | 26.64 | 6900 | 0.8540 | 48.0544 |
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- | 0.0001 | 27.03 | 7000 | 0.8605 | 48.5390 |
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- | 0.0001 | 27.41 | 7100 | 0.8613 | 48.9226 |
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- | 0.0001 | 27.8 | 7200 | 0.8673 | 48.9491 |
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- | 0.0001 | 28.19 | 7300 | 0.8688 | 48.7936 |
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- | 0.0001 | 28.57 | 7400 | 0.8711 | 48.8350 |
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- | 0.0001 | 28.96 | 7500 | 0.8728 | 48.8581 |
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- | 0.0001 | 29.34 | 7600 | 0.8736 | 49.8454 |
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- | 0.0001 | 29.73 | 7700 | 0.8759 | 49.9248 |
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- | 0.0001 | 30.12 | 7800 | 0.8786 | 49.6932 |
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- | 0.0001 | 30.5 | 7900 | 0.8809 | 49.7429 |
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- | 0.0001 | 30.89 | 8000 | 0.8826 | 49.9132 |
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- | 0.0001 | 31.27 | 8100 | 0.8840 | 50.4506 |
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- | 0.0001 | 31.66 | 8200 | 0.8859 | 50.2919 |
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- | 0.0001 | 32.05 | 8300 | 0.8888 | 50.5532 |
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- | 0.0001 | 32.43 | 8400 | 0.8924 | 50.6491 |
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- | 0.0001 | 32.82 | 8500 | 0.8928 | 50.9997 |
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- | 0.0001 | 33.2 | 8600 | 0.8920 | 51.3188 |
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- | 0.0001 | 33.59 | 8700 | 0.8946 | 51.1419 |
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- | 0.0001 | 33.98 | 8800 | 0.8956 | 51.1551 |
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- | 0.0001 | 34.36 | 8900 | 0.8988 | 50.7483 |
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- | 0.0001 | 34.75 | 9000 | 0.9003 | 50.8889 |
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- | 0.0001 | 35.14 | 9100 | 0.9011 | 50.9302 |
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- | 0.0001 | 35.52 | 9200 | 0.9020 | 50.9533 |
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- | 0.0001 | 35.91 | 9300 | 0.9019 | 51.5603 |
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- | 0.0001 | 36.29 | 9400 | 0.9033 | 51.6479 |
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- | 0.0001 | 36.68 | 9500 | 0.9040 | 51.6810 |
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- | 0.0001 | 37.07 | 9600 | 0.9049 | 51.6744 |
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- | 0.0001 | 37.45 | 9700 | 0.9053 | 51.6429 |
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- | 0.0001 | 37.84 | 9800 | 0.9057 | 51.5966 |
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- | 0.0001 | 38.22 | 9900 | 0.9060 | 51.7372 |
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- | 0.0001 | 38.61 | 10000 | 0.9061 | 51.3701 |
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  ### Framework versions
 
2
  language:
3
  - fa
4
  license: apache-2.0
5
+ base_model: makhataei/Whisper-Small-Common-Voice
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  tags:
7
  - fa-asr
8
  - generated_from_trainer
 
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  # Whisper Small Persian
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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 Common Voice 15.0 dataset.
24
  It achieves the following results on the evaluation set:
25
+ - Loss: 0.8843
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+ - Wer: 48.6448
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28
  ## Model description
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58
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
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+ | 0.1801 | 0.39 | 100 | 0.4976 | 49.1260 |
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+ | 0.1597 | 0.79 | 200 | 0.4624 | 46.7497 |
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+ | 0.0776 | 1.18 | 300 | 0.4794 | 43.1761 |
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+ | 0.083 | 1.57 | 400 | 0.4823 | 43.8028 |
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+ | 0.0786 | 1.96 | 500 | 0.4883 | 44.3915 |
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+ | 0.0331 | 2.36 | 600 | 0.5385 | 46.2437 |
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+ | 0.0353 | 2.75 | 700 | 0.5605 | 44.9439 |
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+ | 0.0139 | 3.14 | 800 | 0.5941 | 45.2812 |
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+ | 0.0152 | 3.53 | 900 | 0.5978 | 49.2930 |
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+ | 0.0155 | 3.93 | 1000 | 0.6114 | 49.9777 |
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+ | 0.0063 | 4.32 | 1100 | 0.6467 | 50.0041 |
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+ | 0.0079 | 4.71 | 1200 | 0.6383 | 48.0875 |
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+ | 0.0046 | 5.1 | 1300 | 0.6500 | 45.4995 |
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+ | 0.0042 | 5.5 | 1400 | 0.6476 | 47.4492 |
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+ | 0.0052 | 5.89 | 1500 | 0.6685 | 52.1870 |
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+ | 0.0023 | 6.28 | 1600 | 0.6794 | 44.2510 |
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+ | 0.0032 | 6.67 | 1700 | 0.6724 | 45.7161 |
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+ | 0.0021 | 7.07 | 1800 | 0.6820 | 47.6013 |
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+ | 0.0015 | 7.46 | 1900 | 0.6925 | 46.6720 |
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+ | 0.0024 | 7.85 | 2000 | 0.7104 | 50.2902 |
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+ | 0.0029 | 8.24 | 2100 | 0.6837 | 46.4173 |
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+ | 0.0016 | 8.64 | 2200 | 0.7191 | 46.0088 |
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+ | 0.0017 | 9.03 | 2300 | 0.7105 | 47.5964 |
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+ | 0.0014 | 9.42 | 2400 | 0.7293 | 44.7603 |
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+ | 0.0018 | 9.81 | 2500 | 0.7365 | 49.8966 |
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+ | 0.0008 | 10.21 | 2600 | 0.7378 | 47.4740 |
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+ | 0.0016 | 10.6 | 2700 | 0.7303 | 45.9691 |
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+ | 0.0011 | 10.99 | 2800 | 0.7330 | 47.7254 |
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+ | 0.0014 | 11.38 | 2900 | 0.7448 | 44.8579 |
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+ | 0.0013 | 11.78 | 3000 | 0.7471 | 46.5116 |
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+ | 0.0015 | 12.17 | 3100 | 0.7513 | 47.5699 |
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+ | 0.0014 | 12.56 | 3200 | 0.7380 | 46.4008 |
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+ | 0.0015 | 12.95 | 3300 | 0.7520 | 45.9658 |
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+ | 0.0009 | 13.35 | 3400 | 0.7482 | 49.2269 |
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+ | 0.0021 | 13.74 | 3500 | 0.7619 | 47.1234 |
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+ | 0.0013 | 14.13 | 3600 | 0.7453 | 49.3956 |
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+ | 0.001 | 14.52 | 3700 | 0.7582 | 47.6741 |
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+ | 0.0009 | 14.92 | 3800 | 0.7637 | 46.9713 |
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+ | 0.0014 | 15.31 | 3900 | 0.7722 | 47.2706 |
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+ | 0.001 | 15.7 | 4000 | 0.7692 | 46.9663 |
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+ | 0.0003 | 16.09 | 4100 | 0.7744 | 47.1730 |
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+ | 0.0004 | 16.49 | 4200 | 0.7842 | 47.3351 |
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+ | 0.0003 | 16.88 | 4300 | 0.7784 | 47.0771 |
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+ | 0.0002 | 17.27 | 4400 | 0.7879 | 45.7641 |
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+ | 0.0005 | 17.66 | 4500 | 0.7965 | 50.0240 |
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+ | 0.0004 | 18.06 | 4600 | 0.8001 | 48.4381 |
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+ | 0.0002 | 18.45 | 4700 | 0.8016 | 49.0037 |
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+ | 0.0002 | 18.84 | 4800 | 0.8066 | 50.0868 |
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+ | 0.0009 | 19.23 | 4900 | 0.8021 | 47.2276 |
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+ | 0.0005 | 19.63 | 5000 | 0.8162 | 47.3500 |
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+ | 0.0003 | 20.02 | 5100 | 0.8091 | 48.7225 |
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+ | 0.0003 | 20.41 | 5200 | 0.8060 | 51.5024 |
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+ | 0.0003 | 20.8 | 5300 | 0.8220 | 51.4875 |
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+ | 0.0003 | 21.2 | 5400 | 0.8098 | 45.8617 |
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+ | 0.0003 | 21.59 | 5500 | 0.8132 | 44.8711 |
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+ | 0.0009 | 21.98 | 5600 | 0.8006 | 45.3937 |
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+ | 0.0003 | 22.37 | 5700 | 0.8008 | 45.6186 |
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+ | 0.0002 | 22.77 | 5800 | 0.8081 | 46.3247 |
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+ | 0.0002 | 23.16 | 5900 | 0.8082 | 46.1279 |
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+ | 0.0002 | 23.55 | 6000 | 0.8238 | 46.1775 |
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+ | 0.0005 | 23.95 | 6100 | 0.8119 | 49.9727 |
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+ | 0.0002 | 24.34 | 6200 | 0.8315 | 49.0863 |
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+ | 0.0001 | 24.73 | 6300 | 0.8224 | 47.2243 |
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+ | 0.0001 | 25.12 | 6400 | 0.8259 | 47.1681 |
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+ | 0.0001 | 25.52 | 6500 | 0.8219 | 48.5737 |
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+ | 0.0002 | 25.91 | 6600 | 0.8400 | 48.9077 |
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+ | 0.0005 | 26.3 | 6700 | 0.8319 | 47.5567 |
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+ | 0.0001 | 26.69 | 6800 | 0.8394 | 50.2357 |
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+ | 0.0001 | 27.09 | 6900 | 0.8480 | 48.4629 |
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+ | 0.0001 | 27.48 | 7000 | 0.8498 | 47.1151 |
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+ | 0.0002 | 27.87 | 7100 | 0.8342 | 48.9243 |
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+ | 0.0003 | 28.26 | 7200 | 0.8184 | 47.3731 |
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+ | 0.0001 | 28.66 | 7300 | 0.8278 | 47.9288 |
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+ | 0.0002 | 29.05 | 7400 | 0.8439 | 47.8610 |
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+ | 0.0001 | 29.44 | 7500 | 0.8461 | 49.9463 |
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+ | 0.0001 | 29.83 | 7600 | 0.8449 | 48.4861 |
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+ | 0.0001 | 30.23 | 7700 | 0.8512 | 49.0003 |
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+ | 0.0001 | 30.62 | 7800 | 0.8555 | 48.2777 |
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+ | 0.0001 | 31.01 | 7900 | 0.8543 | 48.6795 |
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+ | 0.0001 | 31.4 | 8000 | 0.8566 | 48.7655 |
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+ | 0.0001 | 31.8 | 8100 | 0.8605 | 48.6779 |
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+ | 0.0 | 32.19 | 8200 | 0.8634 | 49.3691 |
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+ | 0.0 | 32.58 | 8300 | 0.8663 | 50.0438 |
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+ | 0.0 | 32.97 | 8400 | 0.8685 | 49.7280 |
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+ | 0.0 | 33.37 | 8500 | 0.8704 | 49.1641 |
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+ | 0.0 | 33.76 | 8600 | 0.8724 | 48.8416 |
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+ | 0.0 | 34.15 | 8700 | 0.8736 | 49.2286 |
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+ | 0.0 | 34.54 | 8800 | 0.8755 | 48.6134 |
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+ | 0.0 | 34.94 | 8900 | 0.8767 | 48.9259 |
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+ | 0.0 | 35.33 | 9000 | 0.8778 | 48.9805 |
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+ | 0.0 | 35.72 | 9100 | 0.8791 | 49.3212 |
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+ | 0.0 | 36.11 | 9200 | 0.8801 | 49.3724 |
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+ | 0.0 | 36.51 | 9300 | 0.8813 | 49.4336 |
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+ | 0.0 | 36.9 | 9400 | 0.8819 | 49.1045 |
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+ | 0.0 | 37.29 | 9500 | 0.8826 | 49.2633 |
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+ | 0.0 | 37.68 | 9600 | 0.8832 | 49.4237 |
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+ | 0.0 | 38.08 | 9700 | 0.8837 | 48.6316 |
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+ | 0.0 | 38.47 | 9800 | 0.8841 | 48.6465 |
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+ | 0.0 | 38.86 | 9900 | 0.8842 | 48.9342 |
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+ | 0.0 | 39.25 | 10000 | 0.8843 | 48.6448 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
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- oid sha256:6ecb99288f3bd45a1d9f276f5d52acce0b6eea2cc551612c04a1ac1d843aed8f
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  size 966995080
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:77ce651e445777c9df154b004876c74a7f58463ef81ef61d0de064ee51d01c14
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  size 966995080