96 lines
2.7 KiB
Markdown
96 lines
2.7 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-medium
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tags:
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- generated_from_trainer
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datasets:
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- generator
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metrics:
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- wer
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model-index:
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- name: whisper-medium_ro-80mel
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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: generator
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type: generator
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config: default
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split: None
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.6935
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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-medium_ro-80mel
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0839
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- Wer: 0.6935
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- Cer: 1.202
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 64
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
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|:-------------:|:------:|:-----:|:------:|:---------------:|:------:|
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| 0.1665 | 0.7723 | 2500 | 0.9148 | 0.0839 | 0.7855 |
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| 0.108 | 1.5443 | 5000 | 2.035 | 0.0722 | 2.1169 |
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| 0.0805 | 2.3163 | 7500 | 2.5247 | 0.0718 | 2.4453 |
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| 0.0589 | 3.0883 | 10000 | 2.8635 | 0.0583 | 2.8751 |
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| 0.0516 | 3.8606 | 12500 | 3.1281 | 0.0511 | 3.2984 |
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| 0.0415 | 4.6326 | 15000 | 3.2897 | 0.0540 | 3.365 |
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| 0.0368 | 5.4047 | 17500 | 0.0543 | 3.4251 | 3.298 |
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| 0.0315 | 6.1767 | 20000 | 0.0559 | 3.2634 | 3.2452 |
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| 0.0316 | 6.9490 | 22500 | 0.0541 | 3.6173 | 3.4674 |
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| 0.0267 | 7.7210 | 25000 | 0.0547 | 3.3599 | 3.2115 |
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"eval_runtime": 113429.374,
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"eval_samples": 27174,
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"eval_samples_per_second": 0.24,
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"eval_steps_per_second": 0.24,
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"test_samples": 12987,
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"train_samples": 207181
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### Framework versions
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- Transformers 4.57.0
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- Pytorch 2.9.1+cu128
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- Datasets 4.4.1
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- Tokenizers 0.22.1
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