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--- |
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license: apache-2.0 |
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base_model: Buseak/md_mt5_1911_v16_deneme |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: md_mt5_1911_v18_retrain |
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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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# md_mt5_1911_v18_retrain |
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This model is a fine-tuned version of [Buseak/md_mt5_1911_v16_deneme](https://huggingface.co/Buseak/md_mt5_1911_v16_deneme) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1754 |
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- Bleu: 0.7623 |
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- Gen Len: 18.7866 |
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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: 4 |
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- eval_batch_size: 4 |
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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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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| |
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| 0.6365 | 1.0 | 1250 | 0.3435 | 0.6788 | 18.7694 | |
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| 0.5732 | 2.0 | 2500 | 0.3064 | 0.7037 | 18.7644 | |
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| 0.5375 | 3.0 | 3750 | 0.2819 | 0.7114 | 18.7706 | |
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| 0.4912 | 4.0 | 5000 | 0.2549 | 0.7237 | 18.77 | |
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| 0.4648 | 5.0 | 6250 | 0.2394 | 0.7354 | 18.772 | |
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| 0.4321 | 6.0 | 7500 | 0.2245 | 0.7335 | 18.7762 | |
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| 0.4159 | 7.0 | 8750 | 0.2131 | 0.7446 | 18.778 | |
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| 0.4044 | 8.0 | 10000 | 0.2030 | 0.7478 | 18.7776 | |
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| 0.3889 | 9.0 | 11250 | 0.1963 | 0.7496 | 18.7852 | |
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| 0.3798 | 10.0 | 12500 | 0.1896 | 0.7524 | 18.7834 | |
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| 0.3733 | 11.0 | 13750 | 0.1836 | 0.757 | 18.7854 | |
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| 0.3623 | 12.0 | 15000 | 0.1803 | 0.7596 | 18.7852 | |
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| 0.3583 | 13.0 | 16250 | 0.1775 | 0.7618 | 18.7878 | |
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| 0.3643 | 14.0 | 17500 | 0.1758 | 0.7616 | 18.7828 | |
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| 0.3609 | 15.0 | 18750 | 0.1754 | 0.7623 | 18.7866 | |
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### Framework versions |
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- Transformers 4.35.2 |
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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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