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--- |
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license: mit |
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base_model: facebook/mbart-large-50 |
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tags: |
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- summarization |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mbart-large-50-finetuned-model-hu_1121 |
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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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# mbart-large-50-finetuned-model-hu_1121 |
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This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6534 |
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- Rouge1: 35.6227 |
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- Rouge2: 13.0189 |
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- Rougel: 22.0402 |
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- Rougelsum: 26.9175 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 2.9553 | 1.0 | 21353 | 2.5450 | 33.3195 | 12.2415 | 21.2029 | 25.3382 | |
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| 2.2811 | 2.0 | 42706 | 2.3570 | 33.6149 | 11.975 | 20.9943 | 25.726 | |
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| 1.9886 | 3.0 | 64059 | 2.3144 | 34.6221 | 12.2867 | 21.7798 | 26.1901 | |
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| 1.7463 | 4.0 | 85412 | 2.3198 | 35.2114 | 12.9183 | 22.215 | 27.1176 | |
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| 1.5245 | 5.0 | 106765 | 2.3774 | 35.1147 | 13.1621 | 22.3167 | 26.9264 | |
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| 1.3222 | 6.0 | 128118 | 2.4642 | 35.5719 | 13.1532 | 22.0023 | 26.8084 | |
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| 1.1456 | 7.0 | 149471 | 2.5673 | 35.9156 | 13.2115 | 22.2552 | 27.2581 | |
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| 1.0087 | 8.0 | 170824 | 2.6534 | 35.6227 | 13.0189 | 22.0402 | 26.9175 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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