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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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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-v2-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: 4.9124219851016715 |
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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/og6v8hvi) |
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# whisper-large-v2-fo-100h-30k-steps |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ravnursson_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0837 |
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- Wer: 4.9124 |
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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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| 0.2336 | 0.2320 | 1000 | 0.2811 | 20.5154 | |
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| 0.1631 | 0.4640 | 2000 | 0.1950 | 15.0191 | |
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| 0.124 | 0.6961 | 3000 | 0.1548 | 12.6334 | |
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| 0.1234 | 0.9281 | 4000 | 0.1323 | 11.0077 | |
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| 0.0568 | 1.1601 | 5000 | 0.1257 | 10.2174 | |
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| 0.0493 | 1.3921 | 6000 | 0.1204 | 9.5380 | |
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| 0.0473 | 1.6241 | 7000 | 0.1123 | 9.2158 | |
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| 0.0489 | 1.8561 | 8000 | 0.1012 | 8.1588 | |
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| 0.0193 | 2.0882 | 9000 | 0.0983 | 7.7159 | |
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| 0.0242 | 2.3202 | 10000 | 0.0933 | 7.1522 | |
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| 0.0171 | 2.5522 | 11000 | 0.0939 | 7.2680 | |
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| 0.0277 | 2.7842 | 12000 | 0.0876 | 7.0364 | |
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| 0.0077 | 3.0162 | 13000 | 0.0890 | 6.2563 | |
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| 0.0102 | 3.2483 | 14000 | 0.0883 | 6.9609 | |
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| 0.0089 | 3.4803 | 15000 | 0.0871 | 6.2110 | |
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| 0.0119 | 3.7123 | 16000 | 0.0854 | 6.4425 | |
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| 0.0109 | 3.9443 | 17000 | 0.0839 | 5.7379 | |
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| 0.0026 | 4.1763 | 18000 | 0.0850 | 5.9946 | |
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| 0.0063 | 4.4084 | 19000 | 0.0878 | 5.9644 | |
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| 0.0039 | 4.6404 | 20000 | 0.0896 | 6.2966 | |
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| 0.0038 | 4.8724 | 21000 | 0.0842 | 5.9895 | |
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| 0.0028 | 5.1044 | 22000 | 0.0811 | 5.7026 | |
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| 0.0021 | 5.3364 | 23000 | 0.0828 | 5.2194 | |
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| 0.0009 | 5.5684 | 24000 | 0.0850 | 5.1792 | |
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| 0.0023 | 5.8005 | 25000 | 0.0826 | 5.1188 | |
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| 0.0005 | 6.0325 | 26000 | 0.0823 | 5.0936 | |
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| 0.0004 | 6.2645 | 27000 | 0.0818 | 4.9225 | |
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| 0.0017 | 6.4965 | 28000 | 0.0839 | 4.9980 | |
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| 0.0002 | 6.7285 | 29000 | 0.0843 | 4.9577 | |
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| 0.0004 | 6.9606 | 30000 | 0.0837 | 4.9124 | |
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### Framework versions |
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- Transformers 4.43.1 |
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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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