Edit model card

Thangnv/my_t5

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

  • Train Loss: 0.4858
  • Train Sparse Categorical Accuracy: 0.8583
  • Validation Loss: 0.4856
  • Validation Sparse Categorical Accuracy: 0.8604
  • Epoch: 9

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:

  • optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Sparse Categorical Accuracy Validation Loss Validation Sparse Categorical Accuracy Epoch
0.7764 0.7851 0.6316 0.8233 0
0.6144 0.8267 0.5740 0.8381 1
0.5726 0.8371 0.5442 0.8455 2
0.5483 0.8431 0.5273 0.8501 3
0.5315 0.8472 0.5156 0.8527 4
0.5187 0.8503 0.5060 0.8554 5
0.5083 0.8529 0.4995 0.8572 6
0.4997 0.8549 0.4955 0.8581 7
0.4923 0.8567 0.4895 0.8596 8
0.4858 0.8583 0.4856 0.8604 9

Framework versions

  • Transformers 4.33.2
  • TensorFlow 2.13.0
  • Datasets 2.14.5
  • Tokenizers 0.13.3
Downloads last month
6
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Thangnv/my_t5

Base model

google-t5/t5-small
Finetuned
(1530)
this model