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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: GeneralNews_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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# GeneralNews_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: 2.9834 |
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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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| 4.1541 | 0.25 | 200 | 3.4209 | |
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| 3.5494 | 0.51 | 400 | 3.1702 | |
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| 3.2618 | 0.76 | 600 | 3.0273 | |
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| 3.5983 | 1.01 | 800 | 2.9550 | |
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| 3.3355 | 1.26 | 1000 | 2.8883 | |
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| 3.4976 | 1.52 | 1200 | 2.8653 | |
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| 3.1001 | 1.77 | 1400 | 2.8543 | |
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| 2.282 | 2.02 | 1600 | 2.7953 | |
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| 2.5724 | 2.27 | 1800 | 2.7866 | |
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| 2.7474 | 2.53 | 2000 | 2.7778 | |
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| 3.0323 | 2.78 | 2200 | 2.7901 | |
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| 2.3032 | 3.03 | 2400 | 2.7641 | |
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| 2.5042 | 3.28 | 2600 | 2.8059 | |
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| 1.9857 | 3.54 | 2800 | 2.7847 | |
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| 2.5909 | 3.79 | 3000 | 2.8045 | |
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| 2.2105 | 4.04 | 3200 | 2.8051 | |
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| 2.1151 | 4.29 | 3400 | 2.8331 | |
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| 1.9858 | 4.55 | 3600 | 2.8292 | |
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| 1.9633 | 4.8 | 3800 | 2.8133 | |
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| 2.0282 | 5.05 | 4000 | 2.8317 | |
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| 2.0988 | 5.3 | 4200 | 2.8781 | |
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| 2.0699 | 5.56 | 4400 | 2.8627 | |
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| 2.1769 | 5.81 | 4600 | 2.8388 | |
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| 1.7436 | 6.06 | 4800 | 2.8899 | |
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| 1.8312 | 6.31 | 5000 | 2.9223 | |
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| 1.841 | 6.57 | 5200 | 2.8970 | |
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| 2.0157 | 6.82 | 5400 | 2.8754 | |
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| 2.1223 | 7.07 | 5600 | 2.8958 | |
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| 1.6103 | 7.32 | 5800 | 2.9247 | |
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| 1.7702 | 7.58 | 6000 | 2.9562 | |
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| 1.537 | 7.83 | 6200 | 2.9597 | |
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| 1.933 | 8.08 | 6400 | 2.9585 | |
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| 1.3947 | 8.33 | 6600 | 2.9841 | |
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| 1.639 | 8.59 | 6800 | 2.9723 | |
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| 1.6441 | 8.84 | 7000 | 2.9770 | |
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| 1.4509 | 9.09 | 7200 | 2.9865 | |
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| 1.6212 | 9.34 | 7400 | 2.9890 | |
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| 1.8013 | 9.6 | 7600 | 2.9877 | |
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| 1.3722 | 9.85 | 7800 | 2.9834 | |
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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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