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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-small
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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_17_0_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 Small 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 17.0 + Romanian speech synthesis
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+ type: VladS159/common_voice_17_0_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: 10.55709542810149
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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 Small Ro - Sarbu Vlad - multi gpu --> 3
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 + Romanian speech synthesis dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1249
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+ - Wer: 10.5571
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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: 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: 48
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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: 600
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+ - training_steps: 6000
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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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+ | 0.2432 | 0.68 | 500 | 0.2134 | 19.7435 |
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+ | 0.137 | 1.36 | 1000 | 0.1532 | 15.5189 |
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+ | 0.0672 | 2.04 | 1500 | 0.1287 | 13.0426 |
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+ | 0.0579 | 2.72 | 2000 | 0.1218 | 12.8659 |
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+ | 0.0307 | 3.4 | 2500 | 0.1183 | 11.9887 |
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+ | 0.0167 | 4.08 | 3000 | 0.1177 | 11.5866 |
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+ | 0.016 | 4.76 | 3500 | 0.1149 | 10.9531 |
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+ | 0.0099 | 5.43 | 4000 | 0.1212 | 10.9713 |
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+ | 0.0058 | 6.11 | 4500 | 0.1216 | 10.8251 |
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+ | 0.0056 | 6.79 | 5000 | 0.1224 | 10.6515 |
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+ | 0.0036 | 7.47 | 5500 | 0.1238 | 10.6211 |
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+ | 0.0035 | 8.15 | 6000 | 0.1249 | 10.5571 |
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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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