UmarRamzan commited on
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End of training

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README.md CHANGED
@@ -1,8 +1,6 @@
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  ---
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- license: mit
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  tags:
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  - generated_from_trainer
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- base_model: facebook/w2v-bert-2.0
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  datasets:
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  - common_voice_17_0
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  metrics:
@@ -11,8 +9,8 @@ model-index:
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  - name: w2v2-bert-urdu
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  results:
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  - task:
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- type: automatic-speech-recognition
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  name: Automatic Speech Recognition
 
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  dataset:
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  name: common_voice_17_0
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  type: common_voice_17_0
@@ -20,9 +18,9 @@ model-index:
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  split: test[:100]
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  args: ur
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  metrics:
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- - type: wer
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- value: 0.6273224043715847
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- name: Wer
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +28,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # w2v2-bert-urdu
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- This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1498
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- - Wer: 0.6273
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  ## Model description
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@@ -52,7 +50,7 @@ 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-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
@@ -60,7 +58,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 32
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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: 500
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  - num_epochs: 2
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  - mixed_precision_training: Native AMP
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@@ -68,17 +66,17 @@ 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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- | 3.5968 | 0.1695 | 50 | 3.1737 | 1.0 |
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- | 3.1414 | 0.3390 | 100 | 2.9666 | 1.0 |
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- | 2.3694 | 0.5085 | 150 | 1.0788 | 0.6525 |
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- | 0.7692 | 0.6780 | 200 | 0.5647 | 0.4186 |
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- | 0.5488 | 0.8475 | 250 | 0.4491 | 0.3486 |
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- | 0.5568 | 1.0169 | 300 | 0.5883 | 0.7388 |
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- | 0.7925 | 1.1864 | 350 | 1.0338 | 0.7967 |
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- | 1.4791 | 1.3559 | 400 | 1.1474 | 0.6251 |
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- | 1.2758 | 1.5254 | 450 | 1.1359 | 0.6251 |
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- | 1.2763 | 1.6949 | 500 | 1.1497 | 0.6273 |
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- | 1.2789 | 1.8644 | 550 | 1.1498 | 0.6273 |
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  ### Framework versions
 
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  ---
 
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  tags:
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  - generated_from_trainer
 
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  datasets:
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  - common_voice_17_0
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  metrics:
 
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  - name: w2v2-bert-urdu
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  results:
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  - task:
 
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  name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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  dataset:
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  name: common_voice_17_0
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  type: common_voice_17_0
 
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  split: test[:100]
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  args: ur
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  metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.3300546448087432
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # w2v2-bert-urdu
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+ This model was trained from scratch on the common_voice_17_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4246
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+ - Wer: 0.3301
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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: 5e-06
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
 
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  - total_train_batch_size: 32
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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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  - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 0.8145 | 0.1695 | 50 | 0.4620 | 0.3421 |
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+ | 0.4364 | 0.3390 | 100 | 0.3969 | 0.2874 |
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+ | 0.418 | 0.5085 | 150 | 0.3697 | 0.2820 |
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+ | 0.402 | 0.6780 | 200 | 0.3627 | 0.2842 |
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+ | 0.3698 | 0.8475 | 250 | 0.3314 | 0.2710 |
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+ | 0.3779 | 1.0169 | 300 | 0.3292 | 0.2852 |
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+ | 0.3167 | 1.1864 | 350 | 0.3230 | 0.2820 |
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+ | 0.3578 | 1.3559 | 400 | 0.3825 | 0.2940 |
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+ | 0.4189 | 1.5254 | 450 | 0.4225 | 0.3104 |
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+ | 0.4803 | 1.6949 | 500 | 0.4248 | 0.3311 |
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+ | 0.4612 | 1.8644 | 550 | 0.4246 | 0.3301 |
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  ### Framework versions
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