EzraWilliam
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End of training
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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base_model: facebook/wav2vec2-large-xlsr-53
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datasets:
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- common_voice_13_0
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metrics:
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- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod19
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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_13_0
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type: common_voice_13_0
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split: test
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args: id
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metrics:
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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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# wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod19
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This model is a fine-tuned version of [facebook/wav2vec2-
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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- seed: 42
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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:
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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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### Framework versions
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-xls-r-300m
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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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- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod19
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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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split: test
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args: id
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metrics:
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- name: Wer
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type: wer
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value: 0.34075405604719766
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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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# wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod19
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) 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: 0.3575
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- Wer: 0.3408
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## Model description
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- seed: 42
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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: 9
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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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| 2.9583 | 1.0 | 278 | 2.9214 | 1.0 |
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| 2.8606 | 2.0 | 556 | 2.7724 | 1.0 |
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| 1.1528 | 3.0 | 834 | 0.6902 | 0.6319 |
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| 0.7003 | 4.0 | 1112 | 0.4844 | 0.4883 |
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| 0.5853 | 5.0 | 1390 | 0.4030 | 0.4158 |
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| 0.4685 | 6.0 | 1668 | 0.3945 | 0.3838 |
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| 0.4273 | 7.0 | 1946 | 0.3824 | 0.3687 |
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| 0.4116 | 8.0 | 2224 | 0.3643 | 0.3474 |
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| 0.3858 | 9.0 | 2502 | 0.3575 | 0.3408 |
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### Framework versions
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model.safetensors
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