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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- google/fleurs |
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- generated_from_trainer |
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datasets: |
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- fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: facebook/wav2vec2-xls-r-1b |
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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: GOOGLE/FLEURS - PS_AF |
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type: fleurs |
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config: ps_af |
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split: test |
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args: 'Config: ps_af, Training split: train+validation, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.9294849931787176 |
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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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# facebook/wav2vec2-xls-r-1b |
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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 GOOGLE/FLEURS - PS_AF dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.1921 |
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- Wer: 0.9295 |
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- Cer: 0.9608 |
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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: 7.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 1000 |
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- training_steps: 1000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
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| 19.9558 | 1.27 | 100 | 3.2660 | 20.9197 | 1.0 | |
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| 19.7186 | 2.53 | 200 | 1.1692 | 19.2447 | 1.0 | |
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| 15.203 | 3.8 | 300 | 0.9687 | 15.0053 | 0.9998 | |
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| 6.4303 | 5.06 | 400 | 0.9911 | 6.5437 | 0.9632 | |
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| 4.5712 | 6.33 | 500 | 0.9546 | 4.9040 | 0.9323 | |
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| 3.3986 | 12.66 | 1000 | 4.1921 | 0.9295 | 0.9608 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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