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--- |
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license: apache-2.0 |
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language: |
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- sl |
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tags: |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-1B-common_voice-sl-ft |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: lv |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 23.26 |
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- name: Test CER |
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type: cer |
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value: 7.95 |
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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 7.0 |
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type: mozilla-foundation/common_voice_7_0 |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 13.59 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 62.71 |
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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: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: sl |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 62.34 |
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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-1B-common_voice-sl-ft |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2112 |
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- Wer: 0.1404 |
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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: 3e-05 |
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- train_batch_size: 32 |
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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: 64 |
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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: 400 |
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- num_epochs: 100 |
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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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| 1.8291 | 12.2 | 500 | 0.5674 | 0.7611 | |
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| 0.0416 | 24.39 | 1000 | 0.3093 | 0.2964 | |
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| 0.0256 | 36.59 | 1500 | 0.2224 | 0.2072 | |
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| 0.0179 | 48.78 | 2000 | 0.2274 | 0.1960 | |
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| 0.0113 | 60.98 | 2500 | 0.2078 | 0.1582 | |
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| 0.0086 | 73.17 | 3000 | 0.1898 | 0.1552 | |
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| 0.0059 | 85.37 | 3500 | 0.2054 | 0.1446 | |
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| 0.0044 | 97.56 | 4000 | 0.2112 | 0.1404 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.10.3 |
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