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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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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 small Luxembourgish |
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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 lb_lu |
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type: google/fleurs |
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config: lb_lu |
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split: test |
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metrics: |
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- name: Wer |
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type: wer |
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value: 39.49904580152672 |
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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 small Luxembourgish |
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This model is a fine-tuned version of [bofenghuang/whisper-small-cv11-german-punct](https://huggingface.co/bofenghuang/whisper-small-cv11-german-punct) on the google/fleurs lb_lu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1857 |
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- Wer: 39.4990 |
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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: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- total_eval_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: 5000 |
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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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| 0.0618 | 38.46 | 500 | 1.0104 | 43.2968 | |
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| 0.0055 | 76.92 | 1000 | 1.0684 | 40.1288 | |
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| 0.0024 | 115.38 | 1500 | 1.1056 | 40.9447 | |
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| 0.0014 | 153.85 | 2000 | 1.1280 | 39.7615 | |
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| 0.0013 | 192.31 | 2500 | 1.1415 | 39.9857 | |
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| 0.0008 | 230.77 | 3000 | 1.1573 | 39.7996 | |
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| 0.0006 | 269.23 | 3500 | 1.1682 | 40.0095 | |
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| 0.0006 | 307.69 | 4000 | 1.1769 | 39.7233 | |
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| 0.0005 | 346.15 | 4500 | 1.1826 | 39.5134 | |
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| 0.0004 | 384.62 | 5000 | 1.1857 | 39.4990 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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