Edit model card

Visualize in Weights & Biases

t5-small-finetuned-xsum

This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:

  • Loss: 3.2350

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: 7
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.229 0.1001 71 3.5533
3.8218 0.2003 142 3.3962
3.6384 0.3004 213 3.3290
3.6616 0.4006 284 3.2940
3.5887 0.5007 355 3.2713
3.6246 0.6008 426 3.2550
3.5184 0.7010 497 3.2448
3.5059 0.8011 568 3.2391
3.5116 0.9013 639 3.2350

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
2
Safetensors
Model size
60.5M params
Tensor type
F32
·
Inference API
Unable to determine this model's library. Check the docs .

Model tree for thainq107/t5-small-finetuned-xsum

Base model

google-t5/t5-small
Finetuned
(1524)
this model

Dataset used to train thainq107/t5-small-finetuned-xsum