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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: flan-t5-small-finetuned-mlsum-tr |
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results: [] |
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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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# flan-t5-small-finetuned-mlsum-tr |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: nan |
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- eval_rouge1: 10.3443 |
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- eval_rouge2: 5.3615 |
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- eval_rougeL: 8.9871 |
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- eval_rougeLsum: 9.3134 |
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- eval_gen_len: 16.1858 |
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- eval_runtime: 378.4208 |
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- eval_samples_per_second: 33.759 |
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- eval_steps_per_second: 2.111 |
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- epoch: 2.0 |
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- step: 31160 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 5 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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