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--- |
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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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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-finetune-hindi-fleurs |
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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: hi_in |
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split: train+test |
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args: hi_in |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.42621638924455824 |
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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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# whisper-tiny-finetune-hindi-fleurs |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8315 |
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- Wer Ortho: 0.4313 |
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- Wer: 0.4262 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 32 |
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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: 50 |
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- training_steps: 500 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
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| 1.8112 | 1.39 | 100 | 1.7274 | 0.6323 | 0.6258 | |
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| 1.0387 | 2.78 | 200 | 1.1194 | 0.5130 | 0.5072 | |
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| 0.7671 | 4.17 | 300 | 0.9671 | 0.4665 | 0.4613 | |
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| 0.5283 | 5.56 | 400 | 0.8840 | 0.4494 | 0.4440 | |
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| 0.4458 | 6.94 | 500 | 0.8315 | 0.4313 | 0.4262 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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