End of training
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README.md
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---
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language:
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- gn
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license: apache-2.0
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metrics:
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- name: Wer
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type: wer
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value:
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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 [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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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:
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- train_batch_size: 8
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- eval_batch_size: 16
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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: constant_with_warmup
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- lr_scheduler_warmup_steps:
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- training_steps:
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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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- Transformers 4.44.
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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---
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library_name: transformers
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language:
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- gn
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license: apache-2.0
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metrics:
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- name: Wer
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type: wer
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value: 39.84010659560293
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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 [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2438
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- Wer: 39.8401
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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-05
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- train_batch_size: 8
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- eval_batch_size: 16
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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: constant_with_warmup
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- lr_scheduler_warmup_steps: 3000
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- training_steps: 3000
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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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| 1.2579 | 0.4955 | 500 | 0.3710 | 53.4310 |
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| 0.919 | 0.9911 | 1000 | 0.3295 | 49.9001 |
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| 0.746 | 1.4866 | 1500 | 0.2902 | 45.1033 |
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| 0.6767 | 1.9822 | 2000 | 0.2674 | 43.3711 |
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| 0.574 | 2.4777 | 2500 | 0.2677 | 42.5716 |
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| 0.5485 | 2.9732 | 3000 | 0.2438 | 39.8401 |
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### Framework versions
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- Transformers 4.44.1
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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