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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-ashok |
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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: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.35301353013530135 |
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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-tiny-ashok |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8440 |
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- Wer Ortho: 34.6847 |
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- Wer: 0.3530 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 50 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 0.0234 | 6.67 | 100 | 0.6639 | 34.2986 | 0.3383 | |
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| 0.003 | 13.33 | 200 | 0.7587 | 33.9768 | 0.3401 | |
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| 0.0005 | 20.0 | 300 | 0.7870 | 34.2342 | 0.3475 | |
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| 0.0003 | 26.67 | 400 | 0.8045 | 35.1351 | 0.3567 | |
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| 0.0002 | 33.33 | 500 | 0.8144 | 35.5856 | 0.3610 | |
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| 0.0001 | 40.0 | 600 | 0.8262 | 35.5212 | 0.3604 | |
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| 0.0001 | 46.67 | 700 | 0.8341 | 35.3282 | 0.3592 | |
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| 0.0001 | 53.33 | 800 | 0.8397 | 35.1995 | 0.3579 | |
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| 0.0001 | 60.0 | 900 | 0.8426 | 34.7490 | 0.3536 | |
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| 0.0001 | 66.67 | 1000 | 0.8440 | 34.6847 | 0.3530 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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