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--- |
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language: |
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- hsb |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_8_0 |
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- generated_from_trainer |
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- hsb |
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- robust-speech-event |
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- model_for_talk |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-hsb-v2 |
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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 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: hsb |
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metrics: |
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- name: Test WER |
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type: wer |
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value: [] |
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- name: Test CER |
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type: cer |
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value: [] |
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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-hsb-v2 |
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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: 0.5328 |
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- Wer: 0.4596 |
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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: 0.00045 |
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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: 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 |
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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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| 8.5979 | 3.23 | 100 | 3.5602 | 1.0 | |
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| 3.303 | 6.45 | 200 | 3.2238 | 1.0 | |
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| 3.2034 | 9.68 | 300 | 3.2002 | 0.9888 | |
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| 2.7986 | 12.9 | 400 | 1.2408 | 0.9210 | |
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| 1.3869 | 16.13 | 500 | 0.7973 | 0.7462 | |
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| 1.0228 | 19.35 | 600 | 0.6722 | 0.6788 | |
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| 0.8311 | 22.58 | 700 | 0.6100 | 0.6150 | |
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| 0.717 | 25.81 | 800 | 0.6236 | 0.6013 | |
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| 0.6264 | 29.03 | 900 | 0.6031 | 0.5575 | |
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| 0.5494 | 32.26 | 1000 | 0.5656 | 0.5309 | |
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| 0.4781 | 35.48 | 1100 | 0.5289 | 0.4996 | |
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| 0.4311 | 38.71 | 1200 | 0.5375 | 0.4768 | |
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| 0.3902 | 41.94 | 1300 | 0.5246 | 0.4703 | |
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| 0.3508 | 45.16 | 1400 | 0.5382 | 0.4696 | |
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| 0.3199 | 48.39 | 1500 | 0.5328 | 0.4596 | |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.2 |
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- Tokenizers 0.11.0 |
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