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--- |
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license: mit |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- ravkuk_summerize_dataset |
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metrics: |
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- rouge |
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model-index: |
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- name: le-fine-tune-mbart-large-50 |
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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: ravkuk_summerize_dataset |
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type: ravkuk_summerize_dataset |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.2928 |
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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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# le-fine-tune-mbart-large-50 |
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This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the ravkuk_summerize_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7762 |
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- Rouge1: 0.2928 |
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- Rouge2: 0.1926 |
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- Rougel: 0.2815 |
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- Rougelsum: 0.2816 |
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- Gen Len: 34.5028 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 3.1169 | 1.0 | 197 | 2.3604 | 0.1878 | 0.0725 | 0.1737 | 0.1737 | 33.7784 | |
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| 1.8945 | 2.0 | 394 | 2.2522 | 0.1897 | 0.0765 | 0.1776 | 0.1776 | 34.2074 | |
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| 1.3083 | 3.0 | 591 | 2.2886 | 0.2001 | 0.0927 | 0.1895 | 0.1892 | 35.4432 | |
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| 0.8693 | 4.0 | 788 | 2.3727 | 0.2243 | 0.1123 | 0.2122 | 0.2117 | 31.4943 | |
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| 0.5507 | 5.0 | 985 | 2.5059 | 0.2577 | 0.1527 | 0.2463 | 0.2466 | 34.3693 | |
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| 0.3385 | 6.0 | 1182 | 2.6032 | 0.2703 | 0.1672 | 0.2593 | 0.2584 | 33.5994 | |
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| 0.2031 | 7.0 | 1379 | 2.6518 | 0.2912 | 0.1932 | 0.2812 | 0.281 | 34.1676 | |
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| 0.1272 | 8.0 | 1576 | 2.7040 | 0.2891 | 0.1895 | 0.2799 | 0.2796 | 34.6761 | |
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| 0.0842 | 9.0 | 1773 | 2.7515 | 0.2978 | 0.198 | 0.2888 | 0.2887 | 34.1932 | |
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| 0.0605 | 10.0 | 1970 | 2.7762 | 0.2928 | 0.1926 | 0.2815 | 0.2816 | 34.5028 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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