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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - scitldr
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: paper-summary
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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: scitldr
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+ type: scitldr
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+ config: Abstract
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+ split: train
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+ args: Abstract
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 0.2967
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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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+ # paper-summary
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the scitldr dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.1243
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+ - Rouge1: 0.2967
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+ - Rouge2: 0.1277
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+ - Rougel: 0.2457
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+ - Rougelsum: 0.2602
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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: 5.6e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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: 8
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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 | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 2.9845 | 1.0 | 63 | 3.2358 | 0.288 | 0.1219 | 0.238 | 0.2522 |
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+ | 2.7469 | 2.0 | 126 | 3.1815 | 0.2922 | 0.1251 | 0.2415 | 0.2562 |
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+ | 2.7032 | 3.0 | 189 | 3.1564 | 0.2991 | 0.1303 | 0.2474 | 0.2619 |
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+ | 2.6479 | 4.0 | 252 | 3.1354 | 0.2973 | 0.1282 | 0.2457 | 0.2608 |
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+ | 2.6303 | 5.0 | 315 | 3.1297 | 0.2964 | 0.1272 | 0.2451 | 0.2598 |
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+ | 2.6115 | 6.0 | 378 | 3.1243 | 0.2967 | 0.1277 | 0.2457 | 0.2602 |
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+ | 2.5704 | 7.0 | 441 | 3.1264 | 0.2967 | 0.127 | 0.2453 | 0.26 |
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+ | 2.6028 | 8.0 | 504 | 3.1252 | 0.2971 | 0.1275 | 0.2456 | 0.2604 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.6.1
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+ - Tokenizers 0.13.1