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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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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: mt5-small-finetuned-cnn_dailymail |
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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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# mt5-small-finetuned-cnn_dailymail |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5244 |
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- Rouge1: 23.8806 |
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- Rouge2: 11.7122 |
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- Rougel: 20.1043 |
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- Rougelsum: 22.5041 |
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- Bleu 1: 3.5889 |
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- Bleu 2: 2.411 |
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- Bleu 3: 1.7466 |
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- Meteor: 11.8919 |
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- Lungime rezumat: 11.496 |
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- Lungime original: 46.991 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu 1 | Bleu 2 | Bleu 3 | Meteor | Lungime rezumat | Lungime original | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:------:|:------:|:------:|:-------:|:---------------:|:----------------:| |
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| 2.9989 | 1.0 | 3583 | 1.6617 | 21.745 | 9.6834 | 17.6 | 20.1315 | 3.1902 | 2.0591 | 1.4759 | 10.57 | 11.408 | 46.991 | |
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| 1.8552 | 2.0 | 7166 | 1.5640 | 22.5336 | 10.3837 | 18.3609 | 20.9449 | 3.2826 | 2.1341 | 1.5187 | 11.0138 | 11.3677 | 46.991 | |
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| 1.7715 | 3.0 | 10749 | 1.5354 | 23.5705 | 11.4281 | 19.7129 | 22.1588 | 3.5276 | 2.3649 | 1.7132 | 11.7397 | 11.4513 | 46.991 | |
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| 1.7385 | 4.0 | 14332 | 1.5244 | 23.8806 | 11.7122 | 20.1043 | 22.5041 | 3.5889 | 2.411 | 1.7466 | 11.8919 | 11.496 | 46.991 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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