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--- |
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language: |
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- en |
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tags: |
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- generated_from_trainer |
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base_model: openai/whisper-small |
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datasets: |
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- QEC |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-small-quartr |
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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: Quartr Earnings Calls |
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type: QEC |
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args: 'config: en, split: test' |
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metrics: |
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- type: wer |
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value: 32.834424695977546 |
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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-small-quartr |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Quartr Earnings Calls dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6429 |
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- Wer: 32.8344 |
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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: 8.120528078446462e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 84 |
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- training_steps: 1500 |
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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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| 0.6771 | 0.32 | 100 | 0.6577 | 25.7437 | |
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| 0.6533 | 0.64 | 200 | 0.6025 | 34.6804 | |
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| 0.5793 | 0.96 | 300 | 0.5784 | 24.3530 | |
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| 0.3872 | 1.28 | 400 | 0.5856 | 32.9592 | |
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| 0.4447 | 1.61 | 500 | 0.5646 | 23.2429 | |
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| 0.414 | 1.93 | 600 | 0.5616 | 70.7016 | |
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| 0.2489 | 2.25 | 700 | 0.5816 | 35.2666 | |
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| 0.2863 | 2.57 | 800 | 0.5853 | 24.7583 | |
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| 0.2698 | 2.89 | 900 | 0.5844 | 32.7409 | |
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| 0.1646 | 3.21 | 1000 | 0.6182 | 27.7892 | |
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| 0.174 | 3.53 | 1100 | 0.6228 | 36.2021 | |
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| 0.2021 | 3.85 | 1200 | 0.6269 | 35.9775 | |
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| 0.2239 | 4.17 | 1300 | 0.6367 | 35.2666 | |
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| 0.1551 | 4.49 | 1400 | 0.6420 | 32.4478 | |
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| 0.1351 | 4.82 | 1500 | 0.6429 | 32.8344 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.1.dev0 |
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- Tokenizers 0.15.2 |
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