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End of training

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  1. README.md +84 -0
  2. generation_config.json +256 -0
README.md ADDED
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+ ---
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+ language:
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+ - ml
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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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+ - generated_from_trainer
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+ datasets:
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+ - thennal/IMaSC
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Small Malayalam - Arjun Shaji
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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: google/fleurs
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+ type: thennal/IMaSC
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+ args: 'config: ml, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 9.54563571143882
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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 Malayalam - Arjun Shaji
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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 google/fleurs dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0209
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+ - Wer: 9.5456
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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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+ - 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: 8000
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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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+ | 0.0433 | 0.5800 | 1000 | 0.0434 | 27.1379 |
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+ | 0.02 | 1.1601 | 2000 | 0.0312 | 20.3733 |
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+ | 0.0169 | 1.7401 | 3000 | 0.0242 | 15.4975 |
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+ | 0.0071 | 2.3202 | 4000 | 0.0217 | 12.3555 |
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+ | 0.0058 | 2.9002 | 5000 | 0.0197 | 11.0646 |
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+ | 0.0022 | 3.4803 | 6000 | 0.0202 | 10.0881 |
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+ | 0.0008 | 4.0603 | 7000 | 0.0204 | 9.7006 |
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+ | 0.0005 | 4.6404 | 8000 | 0.0209 | 9.5456 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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