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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - hi
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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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+ - 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 Small Ori vi
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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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+ args: 'config: hi, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 17.65774934574004
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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 Ori vi
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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 11.0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3950
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+ - Wer: 17.6577
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - training_steps: 1300
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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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+ | 1.1125 | 0.0667 | 30 | 0.9877 | 30.4667 |
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+ | 0.9337 | 0.1333 | 60 | 0.7582 | 18.3338 |
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+ | 0.7185 | 0.2 | 90 | 0.4716 | 16.3129 |
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+ | 0.493 | 0.2667 | 120 | 0.4382 | 16.1893 |
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+ | 0.4328 | 0.3333 | 150 | 0.4298 | 15.6223 |
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+ | 0.4127 | 0.4 | 180 | 0.4208 | 16.8726 |
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+ | 0.3865 | 0.4667 | 210 | 0.4171 | 20.0422 |
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+ | 0.419 | 0.5333 | 240 | 0.4141 | 17.0835 |
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+ | 0.4141 | 0.6 | 270 | 0.4157 | 15.8258 |
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+ | 0.464 | 0.6667 | 300 | 0.4077 | 16.9235 |
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+ | 0.4303 | 0.7333 | 330 | 0.4043 | 18.4865 |
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+ | 0.4418 | 0.8 | 360 | 0.4050 | 16.7999 |
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+ | 0.4786 | 0.8667 | 390 | 0.3981 | 15.1352 |
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+ | 0.4238 | 0.9333 | 420 | 0.3953 | 17.0907 |
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+ | 0.3986 | 1.0 | 450 | 0.3926 | 16.7054 |
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+ | 0.2304 | 1.0667 | 480 | 0.3948 | 16.3928 |
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+ | 0.2583 | 1.1333 | 510 | 0.3943 | 16.6327 |
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+ | 0.2385 | 1.2 | 540 | 0.3997 | 15.1425 |
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+ | 0.2126 | 1.2667 | 570 | 0.3985 | 15.0552 |
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+ | 0.2259 | 1.3333 | 600 | 0.3970 | 16.5964 |
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+ | 0.2237 | 1.4 | 630 | 0.3964 | 16.5382 |
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+ | 0.2344 | 1.4667 | 660 | 0.3983 | 17.9485 |
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+ | 0.2068 | 1.5333 | 690 | 0.3974 | 17.9703 |
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+ | 0.2535 | 1.6 | 720 | 0.3950 | 17.6577 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.4.0
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.0
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