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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ravnursson_asr |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-large-fo-100h-30k-steps |
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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: ravnursson_asr |
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type: ravnursson_asr |
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config: ravnursson_asr |
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split: test |
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args: ravnursson_asr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 4.957720958324945 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/woejhwzd) |
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# whisper-large-fo-100h-30k-steps |
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the ravnursson_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0872 |
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- Wer: 4.9577 |
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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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- 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: 30000 |
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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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| 0.2261 | 0.2320 | 1000 | 0.2668 | 20.1379 | |
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| 0.1577 | 0.4640 | 2000 | 0.1840 | 15.0997 | |
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| 0.1205 | 0.6961 | 3000 | 0.1456 | 11.9489 | |
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| 0.1151 | 0.9281 | 4000 | 0.1300 | 10.6906 | |
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| 0.0457 | 1.1601 | 5000 | 0.1241 | 9.7745 | |
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| 0.0423 | 1.3921 | 6000 | 0.1221 | 9.4876 | |
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| 0.0428 | 1.6241 | 7000 | 0.1080 | 8.4709 | |
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| 0.0486 | 1.8561 | 8000 | 0.1053 | 8.5011 | |
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| 0.0205 | 2.0882 | 9000 | 0.1014 | 7.4643 | |
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| 0.0184 | 2.3202 | 10000 | 0.1003 | 8.1387 | |
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| 0.0165 | 2.5522 | 11000 | 0.0969 | 7.1472 | |
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| 0.025 | 2.7842 | 12000 | 0.0907 | 6.8804 | |
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| 0.0048 | 3.0162 | 13000 | 0.0936 | 6.9005 | |
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| 0.0092 | 3.2483 | 14000 | 0.0923 | 6.7244 | |
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| 0.006 | 3.4803 | 15000 | 0.0921 | 6.3519 | |
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| 0.0095 | 3.7123 | 16000 | 0.0922 | 6.3821 | |
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| 0.0089 | 3.9443 | 17000 | 0.0929 | 6.3771 | |
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| 0.0023 | 4.1763 | 18000 | 0.0915 | 6.0650 | |
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| 0.0033 | 4.4084 | 19000 | 0.0924 | 5.9543 | |
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| 0.0028 | 4.6404 | 20000 | 0.0909 | 5.9040 | |
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| 0.0021 | 4.8724 | 21000 | 0.0884 | 5.7328 | |
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| 0.002 | 5.1044 | 22000 | 0.0874 | 5.4057 | |
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| 0.0008 | 5.3364 | 23000 | 0.0890 | 5.3654 | |
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| 0.0005 | 5.5684 | 24000 | 0.0857 | 5.2597 | |
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| 0.002 | 5.8005 | 25000 | 0.0860 | 5.2144 | |
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| 0.0007 | 6.0325 | 26000 | 0.0873 | 5.1842 | |
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| 0.0002 | 6.2645 | 27000 | 0.0850 | 4.9879 | |
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| 0.001 | 6.4965 | 28000 | 0.0889 | 4.9376 | |
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| 0.0001 | 6.7285 | 29000 | 0.0878 | 5.0081 | |
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| 0.0003 | 6.9606 | 30000 | 0.0872 | 4.9577 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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