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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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- hf-asr-leaderboard |
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- ps |
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- Pashto |
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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-300m |
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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: 0.5137278308321964 |
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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-300m |
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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 GOOGLE/FLEURS - PS_AF dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9154 |
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- Wer: 0.5137 |
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- Cer: 0.1966 |
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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: 2000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 5.0767 | 6.33 | 500 | 4.8783 | 1.0 | 1.0 | |
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| 3.1156 | 12.66 | 1000 | 3.0990 | 1.0 | 1.0 | |
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| 1.3506 | 18.99 | 1500 | 1.1056 | 0.7031 | 0.2889 | |
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| 0.9997 | 25.32 | 2000 | 0.9191 | 0.5944 | 0.2301 | |
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| 0.7838 | 31.65 | 2500 | 0.8952 | 0.5556 | 0.2152 | |
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| 0.6665 | 37.97 | 3000 | 0.8908 | 0.5252 | 0.2017 | |
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| 0.6265 | 44.3 | 3500 | 0.9063 | 0.5133 | 0.1954 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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