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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-bretonwelsh-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: cy |
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split: test |
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args: cy |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.29761332022507164 |
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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-bretonwelsh-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: 0.4506 |
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- Wer: 0.2976 |
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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: 0.0004 |
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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: 10 |
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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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| 2.9503 | 0.98 | 800 | 0.8330 | 0.7296 | |
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| 0.6531 | 1.95 | 1600 | 0.5592 | 0.5470 | |
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| 0.4637 | 2.93 | 2400 | 0.4711 | 0.4539 | |
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| 0.3449 | 3.91 | 3200 | 0.4484 | 0.4116 | |
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| 0.2694 | 4.88 | 4000 | 0.4313 | 0.3860 | |
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| 0.2087 | 5.86 | 4800 | 0.4115 | 0.3616 | |
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| 0.1649 | 6.84 | 5600 | 0.4105 | 0.3378 | |
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| 0.1313 | 7.81 | 6400 | 0.4409 | 0.3236 | |
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| 0.1079 | 8.79 | 7200 | 0.4402 | 0.3093 | |
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| 0.0897 | 9.77 | 8000 | 0.4506 | 0.2976 | |
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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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