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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: speech-synth-large-finetune |
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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/neuronbit-tech/finetune_speech_synth_imperative_train/runs/8cz6mjjm) |
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# speech-synth-large-finetune |
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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: 0.4259 |
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- Wer: 16.8396 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 0.1313 | 0.7800 | 250 | 0.4953 | 30.7145 | |
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| 0.0531 | 1.5585 | 500 | 0.4647 | 28.1055 | |
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| 0.0269 | 2.3370 | 750 | 0.4448 | 19.9526 | |
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| 0.0101 | 3.1154 | 1000 | 0.4392 | 23.0062 | |
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| 0.0064 | 3.8955 | 1250 | 0.4053 | 22.2947 | |
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| 0.0057 | 4.6739 | 1500 | 0.4148 | 19.3003 | |
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| 0.0044 | 5.4524 | 1750 | 0.4028 | 17.9958 | |
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| 0.0047 | 6.2309 | 2000 | 0.4125 | 19.0631 | |
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| 0.003 | 7.0094 | 2250 | 0.3979 | 17.7883 | |
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| 0.0038 | 7.7894 | 2500 | 0.3923 | 20.5455 | |
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| 0.0 | 8.5679 | 2750 | 0.4077 | 17.6401 | |
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| 0.0002 | 9.3463 | 3000 | 0.4050 | 17.3733 | |
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| 0.0009 | 10.1248 | 3250 | 0.4101 | 17.0471 | |
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| 0.0005 | 10.9048 | 3500 | 0.4227 | 17.1954 | |
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| 0.0 | 11.6833 | 3750 | 0.4217 | 17.2250 | |
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| 0.0002 | 12.4618 | 4000 | 0.4241 | 17.0471 | |
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| 0.0 | 13.2402 | 4250 | 0.4239 | 16.9582 | |
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| 0.0005 | 14.0187 | 4500 | 0.4250 | 16.6617 | |
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| 0.0 | 14.7988 | 4750 | 0.4254 | 16.8396 | |
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| 0.0001 | 15.5772 | 5000 | 0.4259 | 16.8396 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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