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--- |
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base_model: ai-forever/ruT5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deabuse |
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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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# deabuse |
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This model is a fine-tuned version of [ai-forever/ruT5-base](https://huggingface.co/ai-forever/ruT5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0760 |
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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: 2e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_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: 1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 5.7858 | 0.05 | 400 | 0.7427 | |
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| 4.3608 | 0.1 | 800 | 0.4047 | |
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| 3.2919 | 0.15 | 1200 | 0.2366 | |
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| 3.2244 | 0.2 | 1600 | 0.2164 | |
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| 3.2491 | 0.25 | 2000 | 0.1757 | |
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| 1.6803 | 0.3 | 2400 | 0.1494 | |
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| 3.2828 | 0.35 | 2800 | 0.1500 | |
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| 3.39 | 0.4 | 3200 | 0.1510 | |
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| 0.0933 | 0.45 | 3600 | 0.1524 | |
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| 3.4757 | 0.5 | 4000 | 0.1423 | |
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| 3.1424 | 0.55 | 4400 | 0.1460 | |
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| 0.9616 | 0.6 | 4800 | 0.1178 | |
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| 2.6271 | 0.65 | 5200 | 0.1178 | |
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| 1.1441 | 0.7 | 5600 | 0.1190 | |
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| 3.018 | 0.75 | 6000 | 0.1136 | |
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| 1.3421 | 0.8 | 6400 | 0.0936 | |
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| 2.3062 | 0.85 | 6800 | 0.0994 | |
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| 2.5594 | 0.9 | 7200 | 0.0945 | |
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| 2.1381 | 0.95 | 7600 | 0.1061 | |
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| 1.0893 | 1.0 | 8000 | 0.1029 | |
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| 0.7525 | 1.05 | 8400 | 0.0978 | |
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| 2.1886 | 1.1 | 8800 | 0.0840 | |
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| 1.9948 | 1.15 | 9200 | 0.0952 | |
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| 0.7933 | 1.2 | 9600 | 0.0871 | |
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| 2.0757 | 1.25 | 10000 | 0.0853 | |
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| 0.6129 | 1.31 | 10400 | 0.0857 | |
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| 0.1338 | 1.36 | 10800 | 0.0936 | |
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| 2.6454 | 1.41 | 11200 | 0.0834 | |
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| 0.4243 | 1.46 | 11600 | 0.0891 | |
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| 0.6615 | 1.51 | 12000 | 0.0885 | |
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| 0.6634 | 1.56 | 12400 | 0.0942 | |
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| 0.5665 | 1.61 | 12800 | 0.0808 | |
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| 0.6661 | 1.66 | 13200 | 0.1021 | |
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| 1.1028 | 1.71 | 13600 | 0.0820 | |
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| 1.5217 | 1.76 | 14000 | 0.0769 | |
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| 0.7644 | 1.81 | 14400 | 0.0771 | |
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| 1.3725 | 1.86 | 14800 | 0.0800 | |
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| 0.846 | 1.91 | 15200 | 0.0788 | |
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| 1.7207 | 1.96 | 15600 | 0.0806 | |
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| 0.9188 | 2.01 | 16000 | 0.0806 | |
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| 1.4303 | 2.06 | 16400 | 0.0814 | |
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| 0.1599 | 2.11 | 16800 | 0.1072 | |
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| 0.1976 | 2.16 | 17200 | 0.0823 | |
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| 0.7077 | 2.21 | 17600 | 0.0830 | |
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| 1.8896 | 2.26 | 18000 | 0.0768 | |
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| 0.6957 | 2.31 | 18400 | 0.0826 | |
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| 0.7827 | 2.36 | 18800 | 0.0802 | |
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| 1.3298 | 2.41 | 19200 | 0.0791 | |
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| 0.2254 | 2.46 | 19600 | 0.0871 | |
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| 1.041 | 2.51 | 20000 | 0.0809 | |
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| 1.5451 | 2.56 | 20400 | 0.0838 | |
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| 1.6318 | 2.61 | 20800 | 0.0801 | |
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| 1.8972 | 2.66 | 21200 | 0.0774 | |
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| 1.8895 | 2.71 | 21600 | 0.0762 | |
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| 0.7721 | 2.76 | 22000 | 0.0740 | |
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| 0.3528 | 2.81 | 22400 | 0.0781 | |
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| 1.325 | 2.86 | 22800 | 0.0770 | |
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| 0.0282 | 2.91 | 23200 | 0.0785 | |
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| 1.6303 | 2.96 | 23600 | 0.0760 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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