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  1. README.md +98 -0
  2. generation_config.json +264 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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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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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-small-ft-client
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: None
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 84.11458333333334
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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-ft-client
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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 audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5990
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+ - Wer: 84.1146
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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: 2
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 16
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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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+ | 0.8044 | 6.37 | 200 | 1.2417 | 69.9219 |
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+ | 0.036 | 12.75 | 400 | 1.1791 | 60.9375 |
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+ | 0.0108 | 19.12 | 600 | 1.3128 | 80.2083 |
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+ | 0.0035 | 25.5 | 800 | 1.3641 | 62.6953 |
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+ | 0.0009 | 31.87 | 1000 | 1.4066 | 66.6016 |
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+ | 0.0004 | 38.25 | 1200 | 1.4410 | 64.5833 |
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+ | 0.0003 | 44.62 | 1400 | 1.4712 | 63.3464 |
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+ | 0.0002 | 51.0 | 1600 | 1.4927 | 63.6068 |
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+ | 0.0002 | 57.37 | 1800 | 1.5102 | 67.1875 |
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+ | 0.0002 | 63.75 | 2000 | 1.5254 | 66.6016 |
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+ | 0.0001 | 70.12 | 2200 | 1.5393 | 77.8646 |
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+ | 0.0001 | 76.49 | 2400 | 1.5512 | 77.9297 |
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+ | 0.0001 | 82.87 | 2600 | 1.5616 | 77.7344 |
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+ | 0.0001 | 89.24 | 2800 | 1.5710 | 83.1380 |
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+ | 0.0001 | 95.62 | 3000 | 1.5791 | 88.0859 |
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+ | 0.0001 | 101.99 | 3200 | 1.5854 | 88.1510 |
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+ | 0.0001 | 108.37 | 3400 | 1.5910 | 88.0859 |
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+ | 0.0001 | 114.74 | 3600 | 1.5953 | 84.1146 |
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+ | 0.0001 | 121.12 | 3800 | 1.5978 | 84.1797 |
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+ | 0.0001 | 127.49 | 4000 | 1.5990 | 84.1146 |
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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+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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