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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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- summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: arxiv27k-t5-abst-title-gen/ |
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results: [] |
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--- |
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# arxiv27k-t5-abst-title-gen/ |
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This model is a fine-tuned version of mt5-small on the arxiv-abstract-title dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6002 |
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- Rouge1: 32.8 |
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- Rouge2: 21.9 |
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- Rougel: 34.8 |
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## Model description |
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Model has been trained with a colab-pro notebook in 4 hours. |
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## Intended uses & limitations |
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Can be used for generating journal titles from given abstracts |
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### Training args |
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model_args = T5Args() |
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model_args.max_seq_length = 256 |
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model_args.train_batch_size = 8 |
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model_args.eval_batch_size = 8 |
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model_args.num_train_epochs = 6 |
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model_args.evaluate_during_training = False |
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model_args.use_multiprocessing = False |
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model_args.fp16 = False |
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model_args.save_steps = 40000 |
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model_args.save_eval_checkpoints = False |
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model_args.save_model_every_epoch = True |
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model_args.output_dir = OUTPUT_DIR |
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model_args.no_cache = True |
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model_args.reprocess_input_data = True |
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model_args.overwrite_output_dir = True |
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model_args.num_return_sequences = 1 |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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### Contact |
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[email protected] |
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Davut Emre Taşar |
