71 lines
2.0 KiB
Markdown
71 lines
2.0 KiB
Markdown
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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-base
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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: whisper-base-gcf
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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-base-gcf
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4385
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- Wer: 100.1274
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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 OptimizerNames.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: 100
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- training_steps: 1500
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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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| 0.9963 | 1.4085 | 200 | 3.4896 | 101.2739 |
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| 0.6015 | 2.8169 | 400 | 3.0877 | 1097.9618 |
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| 0.3216 | 4.2254 | 600 | 2.8618 | 99.7452 |
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| 0.2368 | 5.6338 | 800 | 2.6891 | 100.1274 |
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| 0.1739 | 7.0423 | 1000 | 2.5483 | 421.6561 |
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| 0.1892 | 8.4507 | 1200 | 2.4829 | 104.5860 |
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| 0.1273 | 9.8592 | 1400 | 2.4358 | 1683.6943 |
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| 0.1256 | 10.5634 | 1500 | 2.4385 | 100.1274 |
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### Framework versions
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- Transformers 5.5.0
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- Pytorch 2.4.1+cu124
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- Datasets 3.6.0
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- Tokenizers 0.22.2
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