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Automatic Speech Recognition
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Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +21 -56
  2. model.safetensors +1 -1
  3. runs/May25_08-09-08_instance-til-team-31/events.out.tfevents.1716624688.instance-til-team-31 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 9.6392
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- - Wer: 1.0
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  ## Model description
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@@ -37,7 +37,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-06
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -45,65 +45,30 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 16
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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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- - num_epochs: 30
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  - mixed_precision_training: Native AMP
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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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- | 9.4478 | 0.57 | 100 | 16.8924 | 1.0004 |
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- | 9.154 | 1.14 | 200 | 16.6262 | 1.0296 |
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- | 8.8049 | 1.71 | 300 | 16.3607 | 1.0433 |
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- | 8.5983 | 2.29 | 400 | 16.0932 | 1.0299 |
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- | 8.391 | 2.86 | 500 | 15.8314 | 1.0258 |
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- | 8.1812 | 3.43 | 600 | 15.5691 | 1.0210 |
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- | 7.8779 | 4.0 | 700 | 15.3143 | 1.0162 |
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- | 7.7962 | 4.57 | 800 | 15.0644 | 1.0095 |
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- | 7.4969 | 5.14 | 900 | 14.8225 | 1.0045 |
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- | 7.2389 | 5.71 | 1000 | 14.5929 | 1.0011 |
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- | 7.1556 | 6.29 | 1100 | 14.3716 | 1.0005 |
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- | 6.8993 | 6.86 | 1200 | 14.1652 | 1.0005 |
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- | 6.7645 | 7.43 | 1300 | 13.9677 | 1.0004 |
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- | 6.4951 | 8.0 | 1400 | 13.7771 | 1.0004 |
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- | 6.4375 | 8.57 | 1500 | 13.5871 | 1.0002 |
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- | 6.2423 | 9.14 | 1600 | 13.3975 | 1.0 |
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- | 6.0098 | 9.71 | 1700 | 13.2079 | 1.0 |
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- | 5.9649 | 10.29 | 1800 | 13.0151 | 1.0 |
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- | 5.7463 | 10.86 | 1900 | 12.8257 | 1.0 |
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- | 5.5924 | 11.43 | 2000 | 12.6365 | 1.0 |
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- | 5.427 | 12.0 | 2100 | 12.4524 | 1.0 |
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- | 5.3501 | 12.57 | 2200 | 12.2706 | 1.0 |
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- | 5.1945 | 13.14 | 2300 | 12.0939 | 1.0 |
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- | 5.0109 | 13.71 | 2400 | 11.9239 | 1.0 |
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- | 4.9798 | 14.29 | 2500 | 11.7596 | 1.0 |
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- | 4.8013 | 14.86 | 2600 | 11.6010 | 1.0 |
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- | 4.7351 | 15.43 | 2700 | 11.4466 | 1.0 |
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- | 4.5813 | 16.0 | 2800 | 11.3010 | 1.0 |
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- | 4.54 | 16.57 | 2900 | 11.1603 | 1.0 |
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- | 4.4236 | 17.14 | 3000 | 11.0255 | 1.0 |
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- | 4.3137 | 17.71 | 3100 | 10.8994 | 1.0 |
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- | 4.2944 | 18.29 | 3200 | 10.7777 | 1.0 |
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- | 4.179 | 18.86 | 3300 | 10.6654 | 1.0 |
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- | 4.1668 | 19.43 | 3400 | 10.5568 | 1.0 |
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- | 4.0301 | 20.0 | 3500 | 10.4562 | 1.0 |
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- | 4.0315 | 20.57 | 3600 | 10.3608 | 1.0 |
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- | 3.9657 | 21.14 | 3700 | 10.2723 | 1.0 |
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- | 3.8779 | 21.71 | 3800 | 10.1908 | 1.0 |
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- | 3.8818 | 22.29 | 3900 | 10.1142 | 1.0 |
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- | 3.8197 | 22.86 | 4000 | 10.0451 | 1.0 |
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- | 3.8041 | 23.43 | 4100 | 9.9809 | 1.0 |
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- | 3.7395 | 24.0 | 4200 | 9.9229 | 1.0 |
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- | 3.7321 | 24.57 | 4300 | 9.8707 | 1.0 |
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- | 3.7191 | 25.14 | 4400 | 9.8233 | 1.0 |
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- | 3.6529 | 25.71 | 4500 | 9.7823 | 1.0 |
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- | 3.6868 | 26.29 | 4600 | 9.7467 | 1.0 |
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- | 3.6413 | 26.86 | 4700 | 9.7163 | 1.0 |
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- | 3.6497 | 27.43 | 4800 | 9.6903 | 1.0 |
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- | 3.608 | 28.0 | 4900 | 9.6701 | 1.0 |
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- | 3.6195 | 28.57 | 5000 | 9.6548 | 1.0 |
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- | 3.6115 | 29.14 | 5100 | 9.6443 | 1.0 |
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- | 3.5798 | 29.71 | 5200 | 9.6392 | 1.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.1078
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+ - Wer: 0.9945
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.005
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  - total_train_batch_size: 16
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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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+ - num_epochs: 10
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  - mixed_precision_training: Native AMP
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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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+ | 3.1667 | 0.57 | 100 | 4.5022 | 0.9941 |
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+ | 2.8372 | 1.14 | 200 | 3.6561 | 0.9989 |
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+ | 2.8065 | 1.71 | 300 | 3.9712 | 0.9943 |
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+ | 2.7851 | 2.29 | 400 | 3.9929 | 0.9941 |
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+ | 2.7765 | 2.86 | 500 | 4.2525 | 0.9942 |
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+ | 2.7666 | 3.43 | 600 | 4.1306 | 0.9941 |
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+ | 2.7647 | 4.0 | 700 | 4.1459 | 0.9941 |
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+ | 2.7572 | 4.57 | 800 | 4.1862 | 0.9944 |
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+ | 2.7506 | 5.14 | 900 | 4.1974 | 0.9948 |
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+ | 2.7481 | 5.71 | 1000 | 4.3590 | 0.9944 |
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+ | 2.7445 | 6.29 | 1100 | 4.1933 | 0.9942 |
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+ | 2.7475 | 6.86 | 1200 | 4.2083 | 0.9948 |
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+ | 2.7431 | 7.43 | 1300 | 4.1181 | 0.9945 |
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+ | 2.7404 | 8.0 | 1400 | 4.1052 | 0.9944 |
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+ | 2.7387 | 8.57 | 1500 | 4.1345 | 0.9945 |
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+ | 2.7365 | 9.14 | 1600 | 4.0646 | 0.9945 |
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+ | 2.7353 | 9.71 | 1700 | 4.1078 | 0.9945 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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