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--- |
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base_model: csebuetnlp/mT5_multilingual_XLSum |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: SadNews_2_20epochs |
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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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# SadNews_2_20epochs |
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This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co./csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2760 |
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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: 2 |
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- eval_batch_size: 2 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 3.3998 | 0.76 | 500 | 2.8591 | |
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| 2.8316 | 1.52 | 1000 | 2.5640 | |
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| 2.3969 | 2.29 | 1500 | 2.4411 | |
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| 1.8762 | 3.05 | 2000 | 2.4241 | |
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| 1.9914 | 3.81 | 2500 | 2.3928 | |
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| 1.8294 | 4.57 | 3000 | 2.4093 | |
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| 1.7505 | 5.34 | 3500 | 2.4674 | |
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| 1.313 | 6.1 | 4000 | 2.5457 | |
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| 1.5311 | 6.86 | 4500 | 2.4944 | |
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| 1.2645 | 7.62 | 5000 | 2.5876 | |
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| 1.0581 | 8.38 | 5500 | 2.6490 | |
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| 1.2508 | 9.15 | 6000 | 2.7311 | |
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| 1.3671 | 9.91 | 6500 | 2.7163 | |
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| 0.9799 | 10.67 | 7000 | 2.7751 | |
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| 1.03 | 11.43 | 7500 | 2.8911 | |
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| 0.8382 | 12.2 | 8000 | 2.9649 | |
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| 1.0784 | 12.96 | 8500 | 2.9205 | |
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| 0.7969 | 13.72 | 9000 | 3.0321 | |
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| 0.7965 | 14.48 | 9500 | 3.0564 | |
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| 0.7737 | 15.24 | 10000 | 3.1322 | |
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| 0.591 | 16.01 | 10500 | 3.1051 | |
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| 0.8767 | 16.77 | 11000 | 3.1922 | |
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| 0.6458 | 17.53 | 11500 | 3.2355 | |
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| 0.591 | 18.29 | 12000 | 3.2301 | |
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| 0.6428 | 19.05 | 12500 | 3.2603 | |
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| 0.7789 | 19.82 | 13000 | 3.2760 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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