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End of training

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README.md ADDED
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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-large
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_1_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-large-english-TG
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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
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+ type: common_voice_1_0
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+ config: en
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+ split: None
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+ args: 'config: en, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 18.00053310232233
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+ ---
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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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+ # whisper-large-english-TG
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+
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+ This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the common_voice dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4494
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+ - Wer: 18.0005
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 8
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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: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 4000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-------:|:----:|:---------------:|:-------:|
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+ | 0.0452 | 2.6350 | 1000 | 0.3455 | 19.6915 |
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+ | 0.0034 | 5.2701 | 2000 | 0.3999 | 17.8823 |
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+ | 0.0005 | 7.9051 | 3000 | 0.4770 | 18.1438 |
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+ | 0.0001 | 10.5402 | 4000 | 0.4494 | 18.0005 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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