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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- navjordj/SNL_summarization |
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model-index: |
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- name: t5-large-snl-2 |
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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: snl-summarization |
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type: snl-summarization |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 35.1506 |
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inference: |
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parameters: |
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max_length: 160 |
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repetition_penalty: 1.2 |
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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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# t5-large-snl-2 |
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This model is a fine-tuned version of [navjordj/t5-large-snl](https://huggingface.co/navjordj/t5-large-snl) on the navjordj/SNL_summarization dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 1.8691 |
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- eval_rouge1: 35.1506 |
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- eval_rouge2: 16.0888 |
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- eval_rougeL: 29.7007 |
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- eval_rougeLsum: 32.4251 |
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- eval_gen_len: 41.5629 |
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- eval_runtime: 261.235 |
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- eval_samples_per_second: 3.135 |
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- eval_steps_per_second: 0.199 |
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- step: 0 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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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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- num_epochs: 20.0 |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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