arielcerdap
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End of training
Browse files- README.md +24 -19
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README.md
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---
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language:
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- en
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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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metrics:
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- wer
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model-index:
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- name:
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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:
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type:
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config:
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split:
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args:
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metrics:
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- name: Wer
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type: wer
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value:
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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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#
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer Ortho:
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- Wer:
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch
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### Framework versions
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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-en
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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: 32.99881936245573
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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-en
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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: 0.8597
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- Wer Ortho: 32.7576
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- Wer: 32.9988
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant_with_warmup
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- lr_scheduler_warmup_steps: 50
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- training_steps: 4000
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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 Ortho | Wer |
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|:-------------:|:--------:|:----:|:---------------:|:---------:|:-------:|
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| 0.0007 | 17.2414 | 500 | 0.6479 | 32.3874 | 32.3495 |
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| 0.0002 | 34.4828 | 1000 | 0.7071 | 32.8809 | 32.9988 |
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| 0.0001 | 51.7241 | 1500 | 0.7428 | 32.7576 | 32.9988 |
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| 0.0001 | 68.9655 | 2000 | 0.7709 | 32.6959 | 32.9398 |
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| 0.0 | 86.2069 | 2500 | 0.7948 | 32.7576 | 33.0579 |
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| 0.0 | 103.4483 | 3000 | 0.8179 | 33.0043 | 33.2349 |
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| 0.0 | 120.6897 | 3500 | 0.8392 | 32.9426 | 33.1759 |
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| 0.0 | 137.9310 | 4000 | 0.8597 | 32.7576 | 32.9988 |
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### Framework versions
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model.safetensors
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