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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-lv-60-espeak-cv-ft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- nb_samtale |
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metrics: |
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- wer |
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model-index: |
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- name: cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme |
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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: nb_samtale |
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type: nb_samtale |
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config: annotations |
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split: test |
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args: annotations |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.7063259628056816 |
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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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# cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme |
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This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](https://huggingface.co/facebook/wav2vec2-lv-60-espeak-cv-ft) on the nb_samtale dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.9174 |
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- Wer: 0.7063 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 50 |
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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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| 3.82 | 16.67 | 100 | 5.2819 | 0.7336 | |
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| 2.8834 | 33.33 | 200 | 4.9424 | 0.7091 | |
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| 2.5387 | 50.0 | 300 | 4.9174 | 0.7063 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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