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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-1b-danish-12h-6k-steps |
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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_17_0 |
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type: common_voice_17_0 |
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config: da |
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split: test |
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args: da |
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metrics: |
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- name: Wer |
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type: wer |
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value: 29.80512727765972 |
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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-xls-r-1b-danish-12h-6k-steps |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4179 |
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- Wer: 29.8051 |
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- Cer: 9.5826 |
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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: 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 3000 |
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- training_steps: 11000 |
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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 | Cer | |
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|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:| |
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| 0.9182 | 5.3333 | 1000 | 0.5134 | 53.0768 | 16.3044 | |
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| 0.2894 | 10.6667 | 2000 | 0.3309 | 35.3529 | 10.9777 | |
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| 0.2917 | 16.0 | 3000 | 0.3877 | 38.0657 | 12.0348 | |
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| 0.1964 | 21.3333 | 4000 | 0.4244 | 36.1713 | 11.4545 | |
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| 0.1227 | 26.6667 | 5000 | 0.4213 | 36.4335 | 11.6030 | |
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| 0.1455 | 32.0 | 6000 | 0.4112 | 34.1412 | 10.9986 | |
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| 0.1005 | 37.3333 | 7000 | 0.4383 | 33.8563 | 10.8228 | |
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| 0.0604 | 42.6667 | 8000 | 0.4381 | 33.0379 | 10.5787 | |
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| 0.0616 | 48.0 | 9000 | 0.4445 | 31.4826 | 10.0955 | |
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| 0.0425 | 53.3333 | 10000 | 0.4412 | 30.7637 | 9.8170 | |
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| 0.0326 | 58.6667 | 11000 | 0.4179 | 29.8051 | 9.5826 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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