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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metrics:
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- wer
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model-index:
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- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
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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:
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type:
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config:
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split: test
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args:
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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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
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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
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer:
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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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| 2.
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| 2.8472 | 6.0 | 756 | 2.8495 | 1.0 |
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| 2.8414 | 7.0 | 882 | 2.8303 | 1.0 |
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| 2.8215 | 8.0 | 1008 | 2.7800 | 1.0 |
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| 2.7687 | 9.0 | 1134 | 2.6640 | 1.0 |
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| 2.5326 | 10.0 | 1260 | 2.3184 | 1.0 |
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### Framework versions
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- Transformers 4.39.
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- Pytorch 2.2.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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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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- wer
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model-index:
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- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
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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: id
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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: 0.9777378318584071
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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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
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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: 1.3207
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- Wer: 0.9777
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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: 5
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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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| No log | 1.0 | 464 | 2.8781 | 1.0 |
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| 3.005 | 2.0 | 928 | 2.5395 | 1.0 |
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| 2.7477 | 3.0 | 1392 | 1.6528 | 0.9993 |
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| 1.9398 | 4.0 | 1856 | 1.3991 | 0.9854 |
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| 1.4528 | 5.0 | 2320 | 1.3207 | 0.9777 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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runs/Apr06_03-17-52_91f2b20a926f/events.out.tfevents.1712373719.91f2b20a926f.243.0
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