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bart-large-xsum-samsum

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: facebook/bart-large-xsum
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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-xsum-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: 54.3742
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+ ---
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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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+
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+ # bart-large-xsum-samsum
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+
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+ This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4330
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+ - Rouge1: 54.3742
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+ - Rouge2: 29.1289
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+ - Rougel: 44.1238
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+ - Gen Len: 29.8973
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len |
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+ |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|
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+ | No log | 0.9989 | 460 | 0.4542 | 53.4662 | 28.4545 | 43.6636 | 29.6174 |
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+ | 0.7083 | 2.0 | 921 | 0.4415 | 53.6674 | 28.8109 | 44.0343 | 29.2665 |
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+ | 0.3748 | 2.9967 | 1380 | 0.4330 | 54.3742 | 29.1289 | 44.1238 | 29.8973 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "BartForConditionalGeneration"
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+ ],
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+ "vocab_size": 50264
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+ }
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