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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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+ - ro
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+ license: apache-2.0
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+ base_model: openai/whisper-medium
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+ tags:
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+ - hf-asr-leaderboard
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+ - generated_from_trainer
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+ datasets:
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+ - VladS159/common_voice_16_1_romanian_speech_synthesis
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Medium Ro - Sarbu Vlad - multi gpu - 3
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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 16.1 + Romanian speech synthesis
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+ type: VladS159/common_voice_16_1_romanian_speech_synthesis
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+ args: 'config: ro, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 5.588342662448284
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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 Medium Ro - Sarbu Vlad - multi gpu - 3
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+
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 16.1 + Romanian speech synthesis dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0795
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+ - Wer: 5.5883
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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: 10
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+ - eval_batch_size: 10
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 3
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+ - total_train_batch_size: 30
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+ - total_eval_batch_size: 30
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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: 1000
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+ - training_steps: 10000
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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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+ | 0.1485 | 0.43 | 500 | 0.1439 | 14.2157 |
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+ | 0.1344 | 0.86 | 1000 | 0.1165 | 11.6208 |
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+ | 0.0745 | 1.3 | 1500 | 0.0930 | 9.7621 |
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+ | 0.0727 | 1.73 | 2000 | 0.0912 | 9.5309 |
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+ | 0.0269 | 2.16 | 2500 | 0.0802 | 8.1468 |
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+ | 0.0284 | 2.59 | 3000 | 0.0807 | 8.2411 |
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+ | 0.0162 | 3.03 | 3500 | 0.0765 | 7.6691 |
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+ | 0.0123 | 3.46 | 4000 | 0.0782 | 7.2159 |
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+ | 0.0199 | 3.89 | 4500 | 0.0794 | 6.9847 |
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+ | 0.0086 | 4.32 | 5000 | 0.0763 | 6.4766 |
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+ | 0.0083 | 4.75 | 5500 | 0.0768 | 6.6196 |
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+ | 0.0037 | 5.19 | 6000 | 0.0813 | 6.4371 |
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+ | 0.0035 | 5.62 | 6500 | 0.0780 | 6.0203 |
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+ | 0.0025 | 6.05 | 7000 | 0.0826 | 6.4340 |
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+ | 0.0032 | 6.48 | 7500 | 0.0763 | 5.7344 |
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+ | 0.0021 | 6.91 | 8000 | 0.0762 | 5.9260 |
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+ | 0.0011 | 7.35 | 8500 | 0.0790 | 5.5914 |
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+ | 0.001 | 7.78 | 9000 | 0.0788 | 5.5245 |
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+ | 0.0004 | 8.21 | 9500 | 0.0785 | 5.5883 |
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+ | 0.0004 | 8.64 | 10000 | 0.0795 | 5.5883 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.1
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