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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: no-voice-clone-large-finetune-test |
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results: [] |
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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/testgokulepiphany/finetune_given_imperative_final/runs/p0thi8mj) |
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# no-voice-clone-large-finetune-test |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4622 |
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- Wer: 20.1897 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 2500 |
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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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| 0.0088 | 4.6729 | 250 | 0.5014 | 21.1681 | |
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| 0.0079 | 9.3458 | 500 | 0.5158 | 29.2321 | |
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| 0.0001 | 14.0187 | 750 | 0.4311 | 23.9253 | |
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| 0.0 | 18.6916 | 1000 | 0.4457 | 20.5752 | |
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| 0.0 | 23.3645 | 1250 | 0.4520 | 20.6048 | |
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| 0.0 | 28.0374 | 1500 | 0.4560 | 20.1897 | |
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| 0.0 | 32.7103 | 1750 | 0.4588 | 20.1601 | |
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| 0.0 | 37.3832 | 2000 | 0.4607 | 20.1304 | |
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| 0.0 | 42.0561 | 2250 | 0.4618 | 20.2490 | |
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| 0.0 | 46.7290 | 2500 | 0.4622 | 20.1897 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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