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ptah23
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whisper-small-af-ZA

Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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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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+ - google/fleurs
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: whisper-small-af-ZA
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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: google/fleurs
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+ config: af_za
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+ split: train+validation
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+ args: af_za
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.36644093303235514
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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-af-ZA
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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: 0.5728
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+ - Wer Ortho: 0.3943
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+ - Wer: 0.3664
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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: 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: 5
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+ - training_steps: 2000
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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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+ | 0.7731 | 1.45 | 100 | 0.7280 | 0.3863 | 0.3740 |
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+ | 0.2103 | 2.9 | 200 | 0.5116 | 0.3859 | 0.3661 |
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+ | 0.0633 | 4.35 | 300 | 0.4967 | 0.3008 | 0.2810 |
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+ | 0.0249 | 5.8 | 400 | 0.5003 | 0.3477 | 0.3299 |
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+ | 0.0143 | 7.25 | 500 | 0.5191 | 0.3660 | 0.3510 |
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+ | 0.0053 | 8.7 | 600 | 0.5149 | 0.3221 | 0.3070 |
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+ | 0.0035 | 10.14 | 700 | 0.5345 | 0.3443 | 0.3266 |
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+ | 0.0027 | 11.59 | 800 | 0.5339 | 0.3344 | 0.3175 |
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+ | 0.0026 | 13.04 | 900 | 0.5435 | 0.3328 | 0.3134 |
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+ | 0.0037 | 14.49 | 1000 | 0.5346 | 0.2714 | 0.2506 |
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+ | 0.0045 | 15.94 | 1100 | 0.5438 | 0.3389 | 0.3220 |
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+ | 0.0028 | 17.39 | 1200 | 0.5588 | 0.2740 | 0.2551 |
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+ | 0.0036 | 18.84 | 1300 | 0.5466 | 0.2702 | 0.2728 |
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+ | 0.0035 | 20.29 | 1400 | 0.5364 | 0.3332 | 0.3119 |
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+ | 0.0056 | 21.74 | 1500 | 0.5608 | 0.2721 | 0.2506 |
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+ | 0.0037 | 23.19 | 1600 | 0.5443 | 0.3027 | 0.2833 |
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+ | 0.0035 | 24.64 | 1700 | 0.5466 | 0.3866 | 0.3631 |
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+ | 0.0024 | 26.09 | 1800 | 0.5628 | 0.3416 | 0.3198 |
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+ | 0.0036 | 27.54 | 1900 | 0.5495 | 0.3122 | 0.2946 |
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+ | 0.0016 | 28.99 | 2000 | 0.5728 | 0.3943 | 0.3664 |
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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.dev0
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+ - Pytorch 1.12.1+cu116
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1