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--- |
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language: |
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- lt |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-lt-finetune |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: 'null' |
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split: None |
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args: 'config: lt, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 28.115930505307517 |
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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-lt-finetune |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3634 |
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- Wer: 28.1159 |
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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: 5e-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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- 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: 250 |
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- training_steps: 4000 |
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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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| 0.399 | 0.9 | 500 | 0.4877 | 49.1790 | |
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| 0.1925 | 1.8 | 1000 | 0.4019 | 39.1325 | |
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| 0.0734 | 2.7 | 1500 | 0.3989 | 37.5581 | |
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| 0.0324 | 3.6 | 2000 | 0.3947 | 32.9662 | |
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| 0.0053 | 5.4 | 3000 | 0.3708 | 29.2808 | |
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| 0.0007 | 7.19 | 4000 | 0.3634 | 28.1159 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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