End of training
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README.md
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name: Common Voice 16
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type: mozilla-foundation/common_voice_16_1
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config: gn
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split:
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args: gn
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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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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size:
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- eval_batch_size: 16
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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: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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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.
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.19.1
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name: Common Voice 16
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type: mozilla-foundation/common_voice_16_1
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config: gn
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split: None
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args: gn
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metrics:
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- name: Wer
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type: wer
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value: 49.766822118587605
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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: 0.3513
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- Wer: 49.7668
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-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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- gradient_accumulation_steps: 2
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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: 50
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:------:|:----:|:---------------:|:-------:|
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| 0.4171 | 1.0152 | 100 | 0.3798 | 55.2965 |
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| 0.3376 | 2.0305 | 200 | 0.3628 | 53.8974 |
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| 0.294 | 3.0457 | 300 | 0.3528 | 52.4983 |
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| 0.2632 | 4.0609 | 400 | 0.3484 | 49.7668 |
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| 0.2459 | 5.0761 | 500 | 0.3513 | 49.7668 |
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### Framework versions
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- Transformers 4.44.0
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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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