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--- |
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license: apache-2.0 |
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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: b29-wav2vec2-large-xls-r-romansh-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: rm-vallader |
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split: test |
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args: rm-vallader |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.231951560316721 |
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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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# b29-wav2vec2-large-xls-r-romansh-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: 0.2967 |
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- Wer: 0.2320 |
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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: 0.0001 |
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- train_batch_size: 4 |
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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: 8 |
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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: 30 |
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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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| 6.3337 | 3.05 | 400 | 2.9529 | 1.0 | |
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| 2.9274 | 6.11 | 800 | 2.8462 | 0.9995 | |
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| 1.0082 | 9.16 | 1200 | 0.3782 | 0.3628 | |
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| 0.2754 | 12.21 | 1600 | 0.3225 | 0.2857 | |
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| 0.168 | 15.27 | 2000 | 0.3102 | 0.2748 | |
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| 0.1198 | 18.32 | 2400 | 0.3077 | 0.2513 | |
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| 0.1053 | 21.37 | 2800 | 0.3086 | 0.2531 | |
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| 0.0829 | 24.43 | 3200 | 0.2985 | 0.2396 | |
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| 0.0726 | 27.48 | 3600 | 0.2967 | 0.2320 | |
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### Framework versions |
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- Transformers 4.26.0 |
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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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