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--- |
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language: |
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- ln |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Lingala - BrainTheos |
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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: Fleurs |
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type: google/fleurs |
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config: ln_cd |
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split: validation |
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args: ln_cd |
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metrics: |
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- name: Wer |
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type: wer |
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value: 25.050916496945007 |
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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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# Whisper Base Lingala - BrainTheos |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7265 |
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- Wer: 25.0509 |
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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: 1e-05 |
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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: 4 |
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- total_train_batch_size: 64 |
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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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- training_steps: 4000 |
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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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| 0.0081 | 21.0 | 1000 | 0.6218 | 29.8710 | |
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| 0.0016 | 42.01 | 2000 | 0.6865 | 25.1188 | |
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| 0.0009 | 63.01 | 3000 | 0.7152 | 24.9151 | |
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| 0.0007 | 85.0 | 4000 | 0.7265 | 25.0509 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.1.dev0 |
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- Tokenizers 0.13.3 |
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