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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/bart-large-cnn |
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tags: |
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- generated_from_trainer |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-large-cnn-samsum |
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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: samsum |
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type: samsum |
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config: samsum |
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split: validation |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.4139 |
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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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# bart-large-cnn-samsum |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3028 |
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- Rouge1: 0.4139 |
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- Rouge2: 0.2105 |
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- Rougel: 0.3191 |
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- Rougelsum: 0.3193 |
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- Gen Len: 60.0134 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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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: 200 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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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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| 2.9128 | 0.4344 | 100 | 0.3621 | 0.3984 | 0.1999 | 0.3038 | 0.3038 | 60.8888 | |
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| 0.3205 | 0.8689 | 200 | 0.3097 | 0.4102 | 0.2138 | 0.3186 | 0.3188 | 60.6345 | |
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| 0.2702 | 1.3033 | 300 | 0.3041 | 0.4159 | 0.211 | 0.3179 | 0.3179 | 60.077 | |
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| 0.251 | 1.7377 | 400 | 0.2964 | 0.4191 | 0.2154 | 0.3229 | 0.3233 | 59.9022 | |
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| 0.2262 | 2.1721 | 500 | 0.3055 | 0.4135 | 0.208 | 0.3178 | 0.3179 | 60.4132 | |
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| 0.1906 | 2.6066 | 600 | 0.3028 | 0.4139 | 0.2105 | 0.3191 | 0.3193 | 60.0134 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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