End of training
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README.md
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language:
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- tr
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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base_model: openai/whisper-tiny
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model-index:
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- name: Whisper Tiny Tr - Canberk Kandemir
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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: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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split: None
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args: 'config: tr, split: test'
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metrics:
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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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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size:
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_steps: 500
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.
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| 0.
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| 0.
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| 0.
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| 0.0672 | 4.43 | 2500 | 0.5366 | 75.9155 |
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### Framework versions
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language:
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- tr
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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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- hf-asr-leaderboard
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- generated_from_trainer
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Tiny Tr - Canberk Kandemir
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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: Common Voice 11.0
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type: mozilla-foundation/common_voice_11_0
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split: None
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args: 'config: tr, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 65.19764801769809
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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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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5050
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- Wer: 65.1976
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine_with_restarts
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- lr_scheduler_warmup_steps: 500
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.373 | 0.89 | 1000 | 0.5859 | 60.4296 |
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| 0.2174 | 1.77 | 2000 | 0.5236 | 49.7332 |
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| 0.1194 | 2.66 | 3000 | 0.5080 | 61.9743 |
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| 0.0832 | 3.54 | 4000 | 0.5050 | 65.1976 |
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### Framework versions
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model.safetensors
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runs/Feb17_10-43-28_a2c1a4b591cc/events.out.tfevents.1708166609.a2c1a4b591cc.2526.0
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