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--- |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: nadsoft/hamsa-v0.1-beta |
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tags: |
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- generated_from_trainer |
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datasets: |
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- nadsoft/nadsoft-meetings-v2 |
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metrics: |
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- wer |
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model-index: |
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- name: Hamsa-meetings |
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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: nadsoft/nadsoft-meetings-v2 |
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type: nadsoft/nadsoft-meetings-v2 |
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metrics: |
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- name: Wer |
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type: wer |
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value: 43.449519230769226 |
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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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# Hamsa-meetings |
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This model is a fine-tuned version of [nadsoft/hamsa-v0.1-beta](https://huggingface.co/nadsoft/hamsa-v0.1-beta) on the nadsoft/nadsoft-meetings-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9346 |
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- Wer Ortho: 43.4495 |
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- Wer: 43.4495 |
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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: 16 |
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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: 500 |
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- training_steps: 2000 |
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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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| 0.4883 | 2.91 | 250 | 0.6170 | 40.2644 | 40.2644 | |
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| 0.1678 | 5.81 | 500 | 0.6893 | 43.6899 | 43.6899 | |
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| 0.0749 | 8.72 | 750 | 0.7367 | 42.0673 | 42.0673 | |
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| 0.0352 | 11.63 | 1000 | 0.7829 | 42.6683 | 42.6683 | |
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| 0.0214 | 14.53 | 1250 | 0.8553 | 43.9904 | 43.9904 | |
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| 0.0146 | 17.44 | 1500 | 0.9061 | 43.3894 | 43.3894 | |
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| 0.0112 | 20.35 | 1750 | 0.9225 | 44.2909 | 44.2909 | |
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| 0.0104 | 23.26 | 2000 | 0.9346 | 43.4495 | 43.4495 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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