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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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base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small
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tags:
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_16_1
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metrics:
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- wer
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model-index:
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- name: Common Voice 16
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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 16
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type: mozilla-foundation/common_voice_16_1
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config: gn
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split: test
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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: 43.15937940761636
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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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should probably proofread and complete it, then remove this comment. -->
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# Common Voice 16
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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: 0.3185
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- Wer: 43.1594
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 16
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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: 1
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- training_steps: 500
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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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| 0.3978 | 1.01 | 100 | 0.3420 | 46.9111 |
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| 0.3263 | 2.02 | 200 | 0.3318 | 46.0931 |
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| 0.28 | 3.03 | 300 | 0.3226 | 44.6827 |
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| 0.2505 | 4.04 | 400 | 0.3173 | 43.9210 |
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| 0.2427 | 5.05 | 500 | 0.3185 | 43.1594 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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