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---
tags:
- generated_from_trainer
datasets:
- xsum
language:
- en
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metrics:
- name: Rouge1
type: rouge
value: 27.7165
---
<!-- 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-small-finetuned-xsum-finetuned-xsum
This model is a fine-tuned version of [st3rl4nce/t5-small-finetuned-xsum](https://huggingface.co/st3rl4nce/t5-small-finetuned-xsum) on the xsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5146
- eval_rouge1: 27.7165
- eval_rouge2: 7.3585
- eval_rougeL: 21.7684
- eval_rougeLsum: 21.7758
- eval_gen_len: 18.8131
- eval_runtime: 667.5713
- eval_samples_per_second: 16.975
- eval_steps_per_second: 1.062
- epoch: 0.01
- step: 113
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3 |