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End of training

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  1. README.md +10 -30
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -5,24 +5,9 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - common_voice_13_0
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- metrics:
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- - wer
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  model-index:
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  - name: wav2vec2-large-xlsr-53-demo-colab
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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_13_0
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- type: common_voice_13_0
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- config: sah
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- split: test
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- args: sah
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- metrics:
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- - name: Wer
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- type: wer
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- value: 0.5838631682636339
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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
@@ -32,8 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8055
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- - Wer: 0.5839
 
 
 
 
 
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  ## Model description
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@@ -60,18 +50,8 @@ 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: 200
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- - num_epochs: 30
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.2123 | 7.02 | 200 | 0.7225 | 0.6387 |
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- | 0.1811 | 14.04 | 400 | 0.7815 | 0.6240 |
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- | 0.1385 | 21.05 | 600 | 0.7848 | 0.6229 |
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- | 0.1098 | 28.07 | 800 | 0.8055 | 0.5839 |
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-
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  ### Framework versions
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  - generated_from_trainer
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  datasets:
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  - common_voice_13_0
 
 
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  model-index:
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  - name: wav2vec2-large-xlsr-53-demo-colab
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
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  It achieves the following results on the evaluation set:
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+ - eval_loss: 0.7543
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+ - eval_wer: 0.6236
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+ - eval_runtime: 134.854
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+ - eval_samples_per_second: 9.418
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+ - eval_steps_per_second: 1.179
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+ - epoch: 35.09
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+ - step: 1000
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  ## Model description
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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: 400
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+ - num_epochs: 100
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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