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--- |
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language: |
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- sv |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- robust-speech-event |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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metrics: |
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- wer |
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- cer |
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base_model: facebook/wav2vec2-xls-r-300m |
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model-index: |
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- name: wav2vec2-xls-r-300m-swedish |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Speech Recognition |
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dataset: |
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name: Common Voice sv-SE |
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type: mozilla-foundation/common_voice_8_0 |
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args: sv-SE |
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metrics: |
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- type: wer |
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value: 24.73 |
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name: Test WER |
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args: |
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learning_rate: 7.5e-05 |
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train_batch_size: 64 |
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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: 128 |
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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: 1000 |
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num_epochs: 50 |
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mixed_precision_training: Native AMP |
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- type: cer |
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value: 7.58 |
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name: Test CER |
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args: |
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learning_rate: 7.5e-05 |
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train_batch_size: 64 |
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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: 128 |
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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: 1000 |
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num_epochs: 50 |
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mixed_precision_training: Native AMP |
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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-Swedish |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3641 |
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- Wer: 0.2473 |
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- Cer: 0.0758 |
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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: 7.5e-05 |
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- train_batch_size: 64 |
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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: 128 |
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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: 1000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 6.1097 | 5.49 | 500 | 3.1422 | 1.0 | 1.0 | |
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| 2.985 | 10.98 | 1000 | 1.7357 | 0.9876 | 0.4125 | |
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| 1.0363 | 16.48 | 1500 | 0.4773 | 0.3510 | 0.1047 | |
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| 0.6111 | 21.97 | 2000 | 0.3937 | 0.2998 | 0.0910 | |
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| 0.4942 | 27.47 | 2500 | 0.3779 | 0.2776 | 0.0844 | |
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| 0.4421 | 32.96 | 3000 | 0.3745 | 0.2630 | 0.0807 | |
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| 0.4018 | 38.46 | 3500 | 0.3685 | 0.2553 | 0.0781 | |
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| 0.3759 | 43.95 | 4000 | 0.3618 | 0.2488 | 0.0761 | |
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| 0.3646 | 49.45 | 4500 | 0.3641 | 0.2473 | 0.0758 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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