---
tags:
- generated_from_trainer
datasets:
- navjordj/SNL_summarization
model-index:
- name: t5-large-snl-2
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: snl-summarization
      type: snl-summarization
    metrics:
      - name: Rouge1
        type: rouge
        value: 35.1506

inference:
  parameters:
    max_length: 160
    repetition_penalty: 1.2


---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-large-snl-2

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.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- step: 0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2