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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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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-breton-colab |
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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: br |
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split: test |
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args: br |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.508994708994709 |
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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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# wav2vec2-large-xls-r-300m-breton-colab |
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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: 1.2344 |
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- Wer: 0.5090 |
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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: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 35 |
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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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| 2.8178 | 3.36 | 1000 | 1.0244 | 0.7207 | |
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| 0.5674 | 6.72 | 2000 | 0.9848 | 0.6341 | |
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| 0.33 | 10.08 | 3000 | 1.0254 | 0.6014 | |
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| 0.2362 | 13.45 | 4000 | 1.1387 | 0.5848 | |
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| 0.1777 | 16.81 | 5000 | 1.2125 | 0.5783 | |
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| 0.1429 | 20.17 | 6000 | 1.1952 | 0.5572 | |
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| 0.1076 | 23.53 | 7000 | 1.2492 | 0.5628 | |
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| 0.0842 | 26.89 | 8000 | 1.2103 | 0.5410 | |
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| 0.0666 | 30.25 | 9000 | 1.2032 | 0.5128 | |
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| 0.051 | 33.61 | 10000 | 1.2344 | 0.5090 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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