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--- |
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language: |
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- br |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_7_0 |
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- robust-speech-event |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: XLS-R-300M - Breton |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: br |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 107.955 |
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- name: Test CER |
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type: cer |
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value: 379.33 |
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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-breton |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6102 |
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- Wer: 0.4455 |
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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: 7e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 50.0 |
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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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| 2.9205 | 3.33 | 500 | 2.8659 | 1.0 | |
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| 1.6403 | 6.67 | 1000 | 0.9440 | 0.7593 | |
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| 1.3483 | 10.0 | 1500 | 0.7580 | 0.6215 | |
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| 1.2255 | 13.33 | 2000 | 0.6851 | 0.5722 | |
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| 1.1139 | 16.67 | 2500 | 0.6409 | 0.5220 | |
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| 1.0688 | 20.0 | 3000 | 0.6245 | 0.5055 | |
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| 0.99 | 23.33 | 3500 | 0.6142 | 0.4874 | |
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| 0.9345 | 26.67 | 4000 | 0.5946 | 0.4829 | |
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| 0.9058 | 30.0 | 4500 | 0.6229 | 0.4704 | |
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| 0.8683 | 33.33 | 5000 | 0.6153 | 0.4666 | |
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| 0.8367 | 36.67 | 5500 | 0.5952 | 0.4542 | |
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| 0.8162 | 40.0 | 6000 | 0.6030 | 0.4541 | |
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| 0.8042 | 43.33 | 6500 | 0.5972 | 0.4485 | |
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| 0.7836 | 46.67 | 7000 | 0.6070 | 0.4497 | |
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| 0.7556 | 50.0 | 7500 | 0.6102 | 0.4455 | |
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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 0.11.0 |
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