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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-large |
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tags: |
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- generated_from_trainer |
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datasets: |
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- background_summ |
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metrics: |
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- rouge |
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model-index: |
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- name: '2023_12_18_08_41_35' |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: background_summ |
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type: background_summ |
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config: background-summ |
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split: validation |
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args: background-summ |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 39.8 |
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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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# 2023_12_18_08_41_35 |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the background_summ dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3928 |
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- Rouge1: 39.8 |
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- Rouge2: 18.8 |
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- Rougel: 26.7 |
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- Rougelsum: 36.1 |
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- Bertscore Precision: 88.4 |
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- Bertscore Recall: 86.8 |
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- Bertscore F1: 87.5 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------------------:|:----------------:|:------------:| |
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| 1.6858 | 1.0 | 714 | 2.0262 | 41.1 | 19.3 | 27.1 | 37.3 | 87.9 | 87.1 | 87.5 | |
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| 1.1309 | 2.0 | 1428 | 2.0889 | 40.8 | 19.6 | 27.3 | 37.1 | 87.8 | 87.1 | 87.4 | |
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| 0.7568 | 3.0 | 2142 | 2.1569 | 40.8 | 19.1 | 27.3 | 37.0 | 87.8 | 87.0 | 87.4 | |
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| 0.6779 | 4.0 | 2856 | 2.1800 | 39.5 | 18.4 | 26.4 | 35.9 | 87.8 | 86.7 | 87.2 | |
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| 0.5567 | 5.0 | 3570 | 2.2454 | 40.1 | 19.0 | 26.8 | 36.6 | 88.2 | 86.8 | 87.4 | |
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| 0.5264 | 6.0 | 4284 | 2.3172 | 38.8 | 18.1 | 26.1 | 35.2 | 88.0 | 86.6 | 87.3 | |
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| 0.5046 | 7.0 | 4998 | 2.3409 | 40.1 | 19.0 | 27.0 | 36.4 | 88.4 | 86.8 | 87.6 | |
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| 0.4465 | 8.0 | 5712 | 2.3751 | 39.8 | 18.7 | 26.7 | 36.1 | 88.4 | 86.7 | 87.6 | |
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| 0.4524 | 9.0 | 6426 | 2.3824 | 40.0 | 19.0 | 27.1 | 36.4 | 88.5 | 86.8 | 87.6 | |
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| 0.4308 | 10.0 | 7140 | 2.3928 | 39.8 | 18.8 | 26.7 | 36.1 | 88.4 | 86.8 | 87.5 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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