Transformers
PyTorch
TensorBoard
ONNX
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use juancavallotti/t5-base-gec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juancavallotti/t5-base-gec with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("juancavallotti/t5-base-gec") model = AutoModelForSeq2SeqLM.from_pretrained("juancavallotti/t5-base-gec") - Notebooks
- Google Colab
- Kaggle
t5-base-gec
This model is a fine-tuned version of t5-base on the None dataset.
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Downloads last month
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