transformers tensorboard safetensors t5 text2text-generation generated_from_trainer dataset:lilferrit/xsum_t5_distillation base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google-t5/t5-small
datasets:
- lilferrit/xsum_t5_distillation
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: xsum_aligned_smallT5
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: lilferrit/xsum_t5_distillation
      type: lilferrit/xsum_t5_distillation
    metrics:
    - type: rouge
      value: 28.6381
      name: Rouge1
---

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# xsum_aligned_smallT5

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the lilferrit/xsum_t5_distillation dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5258
- Rouge1: 28.6381
- Rouge2: 7.1512
- Rougel: 21.3477
- Rougelsum: 21.2928
- Gen Len: 27.92

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 200

### Training results



### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
