Model save
Browse files- README.md +66 -0
- adapter_model.safetensors +1 -1
README.md
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---
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library_name: peft
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license: mit
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base_model: openai/whisper-large-v3-turbo
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tags:
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- generated_from_trainer
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model-index:
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- name: whisper-turbo-tr_All_datasets_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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# whisper-turbo-tr_All_datasets_finetune
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1497
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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: 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_ratio: 0.1
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- num_epochs: 3
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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 |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.1651 | 0.4869 | 1500 | 0.1745 |
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| 0.158 | 0.9737 | 3000 | 0.1590 |
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| 0.1391 | 1.4606 | 4500 | 0.1540 |
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| 0.1509 | 1.9474 | 6000 | 0.1516 |
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| 0.1387 | 2.4343 | 7500 | 0.1500 |
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| 0.1428 | 2.9211 | 9000 | 0.1497 |
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### Framework versions
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- PEFT 0.15.1
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- Transformers 4.48.0
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- Pytorch 2.5.1
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- Datasets 3.0.0
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- Tokenizers 0.21.1
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 39355784
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version https://git-lfs.github.com/spec/v1
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size 39355784
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