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--- |
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library_name: transformers |
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base_model: Mehrdad-S/common_voice_clone |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: common_voice_clone_continued |
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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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# common_voice_clone_continued |
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This model is a fine-tuned version of [Mehrdad-S/common_voice_clone](https://huggingface.co/Mehrdad-S/common_voice_clone) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4442 |
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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: 3e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 5000 |
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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 | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 0.4885 | 0.4002 | 100 | 0.4510 | |
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| 0.486 | 0.8004 | 200 | 0.4516 | |
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| 0.4836 | 1.2041 | 300 | 0.4500 | |
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| 0.4803 | 1.6043 | 400 | 0.4493 | |
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| 0.4873 | 2.0080 | 500 | 0.4510 | |
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| 0.4833 | 2.4082 | 600 | 0.4495 | |
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| 0.4869 | 2.8084 | 700 | 0.4486 | |
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| 0.4802 | 3.2121 | 800 | 0.4488 | |
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| 0.4758 | 3.6123 | 900 | 0.4470 | |
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| 0.4879 | 4.0160 | 1000 | 0.4472 | |
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| 0.4825 | 4.4162 | 1100 | 0.4480 | |
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| 0.4727 | 4.8164 | 1200 | 0.4457 | |
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| 0.4777 | 5.2201 | 1300 | 0.4485 | |
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| 0.4854 | 5.6203 | 1400 | 0.4488 | |
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| 0.4881 | 6.0240 | 1500 | 0.4472 | |
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| 0.481 | 6.4242 | 1600 | 0.4472 | |
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| 0.474 | 6.8244 | 1700 | 0.4471 | |
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| 0.4836 | 7.2281 | 1800 | 0.4468 | |
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| 0.4852 | 7.6283 | 1900 | 0.4480 | |
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| 0.479 | 8.0320 | 2000 | 0.4449 | |
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| 0.4805 | 8.4322 | 2100 | 0.4463 | |
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| 0.4743 | 8.8324 | 2200 | 0.4477 | |
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| 0.4792 | 9.2361 | 2300 | 0.4473 | |
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| 0.475 | 9.6363 | 2400 | 0.4451 | |
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| 0.4878 | 10.0400 | 2500 | 0.4456 | |
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| 0.478 | 10.4402 | 2600 | 0.4461 | |
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| 0.4805 | 10.8404 | 2700 | 0.4453 | |
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| 0.4773 | 11.2441 | 2800 | 0.4459 | |
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| 0.48 | 11.6443 | 2900 | 0.4453 | |
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| 0.479 | 12.0480 | 3000 | 0.4448 | |
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| 0.475 | 12.4482 | 3100 | 0.4437 | |
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| 0.4752 | 12.8484 | 3200 | 0.4461 | |
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| 0.4767 | 13.2521 | 3300 | 0.4434 | |
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| 0.4739 | 13.6523 | 3400 | 0.4458 | |
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| 0.4762 | 14.0560 | 3500 | 0.4431 | |
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| 0.4722 | 14.4562 | 3600 | 0.4450 | |
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| 0.4742 | 14.8564 | 3700 | 0.4442 | |
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| 0.4809 | 15.2601 | 3800 | 0.4448 | |
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| 0.475 | 15.6603 | 3900 | 0.4457 | |
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| 0.4789 | 16.0640 | 4000 | 0.4454 | |
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| 0.4709 | 16.4642 | 4100 | 0.4450 | |
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| 0.4826 | 16.8644 | 4200 | 0.4454 | |
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| 0.4735 | 17.2681 | 4300 | 0.4446 | |
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| 0.4727 | 17.6683 | 4400 | 0.4433 | |
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| 0.4867 | 18.0720 | 4500 | 0.4450 | |
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| 0.4804 | 18.4722 | 4600 | 0.4427 | |
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| 0.4802 | 18.8724 | 4700 | 0.4448 | |
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| 0.4798 | 19.2761 | 4800 | 0.4459 | |
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| 0.4788 | 19.6763 | 4900 | 0.4438 | |
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| 0.4772 | 20.0800 | 5000 | 0.4442 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.3.1 |
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- Tokenizers 0.21.0 |
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