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--- |
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license: mit |
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base_model: facebook/w2v-bert-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: pashto-asr-v3 |
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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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# pashto-asr-v3 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1448 |
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- Wer: 0.1396 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 1300 |
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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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| 2.9698 | 0.8089 | 100 | 2.8928 | 0.9991 | |
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| 0.8095 | 1.6178 | 200 | 0.6035 | 0.4036 | |
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| 0.6152 | 2.4267 | 300 | 0.4857 | 0.3593 | |
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| 0.3951 | 3.2356 | 400 | 0.4661 | 0.3505 | |
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| 0.5493 | 4.0445 | 500 | 0.3651 | 0.2779 | |
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| 0.4588 | 4.8534 | 600 | 0.3244 | 0.2632 | |
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| 0.3616 | 5.6623 | 700 | 0.2954 | 0.2490 | |
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| 0.1938 | 6.4712 | 800 | 0.2655 | 0.2341 | |
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| 0.2047 | 7.2801 | 900 | 0.2510 | 0.2022 | |
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| 0.2596 | 8.0890 | 1000 | 0.1953 | 0.1756 | |
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| 0.1871 | 8.8979 | 1100 | 0.1716 | 0.1642 | |
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| 0.0768 | 9.7068 | 1200 | 0.1559 | 0.1554 | |
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| 0.1021 | 10.5157 | 1300 | 0.1448 | 0.1396 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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