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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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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: wav2vec2-large-xlsr-53-sw-ke-tokenizer |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: fleurs |
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type: fleurs |
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config: sw_ke |
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split: test |
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args: sw_ke |
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metrics: |
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- type: wer |
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value: 0.6223628691983122 |
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name: Wer |
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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-xlsr-53-sw-ke-tokenizer |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9600 |
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- Wer: 0.6224 |
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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: 0.0003 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 30 |
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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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| 5.8918 | 4.1667 | 400 | 2.8681 | 1.0 | |
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| 2.8863 | 8.3333 | 800 | 2.8663 | 1.0 | |
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| 2.8092 | 12.5 | 1200 | 2.5442 | 1.0 | |
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| 0.8899 | 16.6667 | 1600 | 0.6992 | 0.6511 | |
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| 0.2577 | 20.8333 | 2000 | 0.8239 | 0.6385 | |
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| 0.1397 | 25.0 | 2400 | 0.8893 | 0.6251 | |
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| 0.0971 | 29.1667 | 2800 | 0.9600 | 0.6224 | |
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### Framework versions |
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- Transformers 4.53.0 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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