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--- |
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language: |
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- ta |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Ta - Bharat Ramanathan |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: mozilla-foundation/common_voice_11_0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ta |
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split: test |
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metrics: |
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- type: wer |
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value: 15.78 |
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name: WER |
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- task: |
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type: automatic-speech-recognition |
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name: 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: ta_in |
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split: test |
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metrics: |
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- type: wer |
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value: 20.41 |
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name: WER |
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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 Base Ta - Bharat Ramanathan |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2269 |
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- Wer: 21.7243 |
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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: 64 |
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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: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 10000 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.5559 | 0.1 | 1000 | 0.3963 | 35.3308 | |
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| 0.3891 | 0.2 | 2000 | 0.3146 | 29.1511 | |
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| 0.3425 | 0.3 | 3000 | 0.2834 | 25.5930 | |
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| 0.3108 | 0.1 | 4000 | 0.2669 | 24.7191 | |
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| 0.2866 | 0.1 | 5000 | 0.2596 | 25.0936 | |
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| 0.2697 | 0.2 | 6000 | 0.2507 | 24.5943 | |
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| 0.2421 | 0.05 | 6500 | 0.2411 | 23.0395 | |
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| 0.2425 | 0.1 | 7000 | 0.2370 | 23.3804 | |
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| 0.2404 | 0.15 | 7500 | 0.2333 | 22.7959 | |
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| 0.2381 | 0.2 | 8000 | 0.2311 | 22.9420 | |
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| 0.2429 | 0.25 | 8500 | 0.2305 | 22.0166 | |
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| 0.2402 | 0.3 | 9000 | 0.2284 | 22.1140 | |
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| 0.2377 | 0.35 | 9500 | 0.2271 | 22.0653 | |
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| 0.2389 | 0.4 | 10000 | 0.2269 | 21.7243 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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