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whisper-tiny-en

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ base_model: openai/whisper-tiny
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - PolyAI/minds14
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper Tiny English
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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: Minds 14
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+ type: PolyAI/minds14
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+ config: en-US
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+ split: train
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+ args: en-US
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.258610624635143
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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 Tiny English
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Minds 14 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4154
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+ - Wer Ortho: 0.2659
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+ - Wer: 0.2586
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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: 32
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+ - eval_batch_size: 16
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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: constant_with_warmup
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+ - lr_scheduler_warmup_steps: 20
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+ - training_steps: 100
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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 Ortho | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
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+ | 4.2901 | 0.33 | 5 | 4.2556 | 0.4220 | 0.2919 |
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+ | 4.3552 | 0.67 | 10 | 3.7784 | 0.4226 | 0.2931 |
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+ | 3.453 | 1.0 | 15 | 2.9546 | 0.4152 | 0.2907 |
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+ | 2.9147 | 1.33 | 20 | 2.4090 | 0.3988 | 0.2931 |
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+ | 2.3042 | 1.67 | 25 | 1.7869 | 0.3701 | 0.3001 |
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+ | 1.6056 | 2.0 | 30 | 1.1284 | 0.3494 | 0.3012 |
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+ | 0.988 | 2.33 | 35 | 0.6892 | 0.3860 | 0.3403 |
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+ | 0.6605 | 2.67 | 40 | 0.5611 | 0.3128 | 0.2849 |
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+ | 0.4645 | 3.0 | 45 | 0.4982 | 0.3091 | 0.2901 |
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+ | 0.4884 | 3.33 | 50 | 0.4640 | 0.2963 | 0.2855 |
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+ | 0.404 | 3.67 | 55 | 0.4453 | 0.2884 | 0.2814 |
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+ | 0.4745 | 4.0 | 60 | 0.4268 | 0.2762 | 0.2697 |
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+ | 0.303 | 4.33 | 65 | 0.4182 | 0.2829 | 0.2720 |
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+ | 0.2717 | 4.67 | 70 | 0.4119 | 0.2829 | 0.2750 |
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+ | 0.3464 | 5.0 | 75 | 0.4080 | 0.2860 | 0.2761 |
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+ | 0.2193 | 5.33 | 80 | 0.4054 | 0.2823 | 0.2750 |
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+ | 0.2138 | 5.67 | 85 | 0.4064 | 0.2762 | 0.2680 |
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+ | 0.1571 | 6.0 | 90 | 0.4102 | 0.2799 | 0.2715 |
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+ | 0.1398 | 6.33 | 95 | 0.4146 | 0.2768 | 0.2697 |
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+ | 0.1523 | 6.67 | 100 | 0.4154 | 0.2659 | 0.2586 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3