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--- |
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library_name: transformers |
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license: mit |
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base_model: catsOfpeople/speecht5_finetuned_emirhan_soomea |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: speecht5_soome-V2 |
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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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# speecht5_soome-V2 |
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This model is a fine-tuned version of [catsOfpeople/speecht5_finetuned_emirhan_soomea](https://huggingface.co/catsOfpeople/speecht5_finetuned_emirhan_soomea) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2695 |
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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: 0.0001 |
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- train_batch_size: 16 |
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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: 128 |
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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: 100 |
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- training_steps: 3500 |
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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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| 0.9648 | 4.5198 | 100 | 0.4308 | |
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| 0.4495 | 9.0395 | 200 | 0.3583 | |
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| 0.384 | 13.5593 | 300 | 0.3418 | |
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| 0.3637 | 18.0791 | 400 | 0.3177 | |
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| 0.3443 | 22.5989 | 500 | 0.3119 | |
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| 0.3366 | 27.1186 | 600 | 0.3099 | |
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| 0.3328 | 31.6384 | 700 | 0.3222 | |
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| 0.3238 | 36.1582 | 800 | 0.3091 | |
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| 0.3196 | 40.6780 | 900 | 0.2960 | |
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| 0.3156 | 45.1977 | 1000 | 0.2977 | |
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| 0.3123 | 49.7175 | 1100 | 0.2960 | |
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| 0.3107 | 54.2373 | 1200 | 0.2904 | |
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| 0.3029 | 58.7571 | 1300 | 0.2891 | |
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| 0.2978 | 63.2768 | 1400 | 0.2904 | |
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| 0.3012 | 67.7966 | 1500 | 0.2855 | |
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| 0.2977 | 72.3164 | 1600 | 0.2863 | |
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| 0.2915 | 76.8362 | 1700 | 0.2855 | |
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| 0.2935 | 81.3559 | 1800 | 0.2853 | |
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| 0.2877 | 85.8757 | 1900 | 0.2794 | |
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| 0.2839 | 90.3955 | 2000 | 0.2820 | |
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| 0.2847 | 94.9153 | 2100 | 0.2781 | |
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| 0.2831 | 99.4350 | 2200 | 0.2799 | |
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| 0.283 | 103.9548 | 2300 | 0.2811 | |
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| 0.2792 | 108.4746 | 2400 | 0.2774 | |
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| 0.2788 | 112.9944 | 2500 | 0.2813 | |
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| 0.2793 | 117.5141 | 2600 | 0.2755 | |
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| 0.2746 | 122.0339 | 2700 | 0.2769 | |
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| 0.2735 | 126.5537 | 2800 | 0.2729 | |
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| 0.2728 | 131.0734 | 2900 | 0.2764 | |
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| 0.2735 | 135.5932 | 3000 | 0.2751 | |
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| 0.2726 | 140.1130 | 3100 | 0.2754 | |
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| 0.2691 | 144.6328 | 3200 | 0.2707 | |
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| 0.2711 | 149.1525 | 3300 | 0.2717 | |
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| 0.2679 | 153.6723 | 3400 | 0.2724 | |
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| 0.2665 | 158.1921 | 3500 | 0.2695 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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