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--- |
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license: apache-2.0 |
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tags: |
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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-atcosim3 |
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results: [] |
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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-atcosim3 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) |
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on the [atco2_atcosim](https://huggingface.co/datasets/luigisaetta/atco2_atcosim) |
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dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0476 |
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- Wer: 0.0198 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_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: 150 |
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- training_steps: 600 |
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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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| 0.8218 | 0.2 | 50 | 0.3785 | 0.1451 | |
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| 0.1429 | 0.39 | 100 | 0.1213 | 0.0714 | |
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| 0.1155 | 0.59 | 150 | 0.0807 | 0.0517 | |
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| 0.0764 | 0.79 | 200 | 0.0652 | 0.0272 | |
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| 0.0724 | 0.98 | 250 | 0.0607 | 0.0393 | |
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| 0.0357 | 1.18 | 300 | 0.0569 | 0.0242 | |
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| 0.03 | 1.38 | 350 | 0.0553 | 0.0243 | |
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| 0.0325 | 1.57 | 400 | 0.0556 | 0.0228 | |
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| 0.03 | 1.77 | 450 | 0.0501 | 0.0242 | |
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| 0.0232 | 1.97 | 500 | 0.0485 | 0.0205 | |
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| 0.0143 | 2.16 | 550 | 0.0480 | 0.0194 | |
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| 0.0105 | 2.36 | 600 | 0.0476 | 0.0198 | |
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### Framework versions |
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- Transformers 4.29.0 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.11.0 |
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