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--- |
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language: |
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- mn |
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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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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Medium MN with custom data - Zagi |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: None |
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args: 'config: mn, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 10.835168000658422 |
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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 Medium MN with custom data - Zagi |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0918 |
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- Wer: 10.8352 |
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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: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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: 500 |
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- training_steps: 4000 |
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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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| 0.5144 | 0.15 | 500 | 0.3790 | 43.5855 | |
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| 0.3922 | 0.3 | 1000 | 0.2215 | 26.4686 | |
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| 0.2435 | 0.46 | 1500 | 0.1774 | 21.2074 | |
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| 0.2275 | 0.61 | 2000 | 0.1451 | 18.1786 | |
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| 0.1447 | 0.76 | 2500 | 0.1279 | 15.7240 | |
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| 0.2028 | 0.91 | 3000 | 0.1065 | 13.0327 | |
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| 0.1068 | 1.06 | 3500 | 0.1002 | 12.2796 | |
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| 0.087 | 1.21 | 4000 | 0.0918 | 10.8352 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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