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--- |
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base_model: openai/whisper-large-v3 |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: whisper-large-v3-genbed-f-model |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: genbed |
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type: genbed |
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config: en |
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split: test |
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metrics: |
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- type: wer |
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value: 48.07 |
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name: WER |
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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-large-v3-genbed-f-model |
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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: 0.5346 |
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- Wer: 33.8051 |
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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: 1.75e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 30000 |
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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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| 1.0784 | 0.6605 | 250 | 0.5140 | 48.6274 | |
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| 0.4405 | 1.3210 | 500 | 0.4665 | 40.7746 | |
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| 0.3641 | 1.9815 | 750 | 0.4253 | 37.1462 | |
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| 0.215 | 2.6420 | 1000 | 0.4413 | 35.1990 | |
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| 0.1871 | 3.3025 | 1250 | 0.4725 | 37.4548 | |
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| 0.1425 | 3.9630 | 1500 | 0.4407 | 34.2520 | |
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| 0.0918 | 4.6235 | 1750 | 0.4618 | 33.9860 | |
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| 0.0821 | 5.2840 | 2000 | 0.4980 | 33.8689 | |
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| 0.0665 | 5.9445 | 2250 | 0.5042 | 32.3367 | |
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| 0.048 | 6.6050 | 2500 | 0.4927 | 33.9860 | |
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| 0.0441 | 7.2655 | 2750 | 0.5449 | 32.0919 | |
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| 0.0387 | 7.9260 | 3000 | 0.5235 | 31.6876 | |
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| 0.0307 | 8.5865 | 3250 | 0.5227 | 31.7408 | |
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| 0.0282 | 9.2470 | 3500 | 0.5682 | 32.3792 | |
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| 0.0288 | 9.9075 | 3750 | 0.5346 | 33.8051 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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