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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- lilferrit/xsum_t5_distillation
metrics:
- rouge
model-index:
- name: xsum_aligned_smallT5
results:
- task:
name: Summarization
type: summarization
dataset:
name: lilferrit/xsum_t5_distillation
type: lilferrit/xsum_t5_distillation
metrics:
- name: Rouge1
type: rouge
value: 28.6381
---
<!-- 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. -->
# 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
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