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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: HappyNews_1_loadbest |
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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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# HappyNews_1_loadbest |
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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: 3.1967 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 4.1092 | 0.29 | 100 | 4.0260 | |
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| 4.3545 | 0.58 | 200 | 3.6022 | |
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| 3.818 | 0.87 | 300 | 3.3815 | |
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| 3.2577 | 1.16 | 400 | 3.2590 | |
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| 3.1005 | 1.45 | 500 | 3.1290 | |
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| 3.0309 | 1.73 | 600 | 3.0690 | |
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| 3.0128 | 2.02 | 700 | 3.0172 | |
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| 2.4054 | 2.31 | 800 | 3.0086 | |
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| 2.7848 | 2.6 | 900 | 3.0103 | |
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| 2.4307 | 2.89 | 1000 | 2.9606 | |
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| 2.3408 | 3.18 | 1100 | 2.9490 | |
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| 2.4232 | 3.47 | 1200 | 2.9333 | |
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| 2.5301 | 3.76 | 1300 | 2.9138 | |
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| 1.9984 | 4.05 | 1400 | 2.9422 | |
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| 2.1215 | 4.34 | 1500 | 2.9620 | |
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| 1.859 | 4.62 | 1600 | 2.9550 | |
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| 1.8986 | 4.91 | 1700 | 2.9654 | |
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| 1.847 | 5.2 | 1800 | 3.0660 | |
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| 1.7843 | 5.49 | 1900 | 3.0169 | |
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| 1.9724 | 5.78 | 2000 | 3.0131 | |
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| 1.6603 | 6.07 | 2100 | 3.0816 | |
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| 1.4024 | 6.36 | 2200 | 3.0947 | |
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| 1.2758 | 6.65 | 2300 | 3.0688 | |
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| 1.7435 | 6.94 | 2400 | 3.0203 | |
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| 1.2973 | 7.23 | 2500 | 3.1221 | |
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| 1.282 | 7.51 | 2600 | 3.1566 | |
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| 1.4837 | 7.8 | 2700 | 3.1047 | |
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| 1.6313 | 8.09 | 2800 | 3.1343 | |
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| 1.4611 | 8.38 | 2900 | 3.1634 | |
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| 1.0115 | 8.67 | 3000 | 3.1751 | |
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| 1.4337 | 8.96 | 3100 | 3.1701 | |
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| 1.1845 | 9.25 | 3200 | 3.1881 | |
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| 1.2019 | 9.54 | 3300 | 3.1998 | |
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| 1.1448 | 9.83 | 3400 | 3.1967 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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