Instructions to use bashyaldhiraj2067/copy_mechanism_model_e1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bashyaldhiraj2067/copy_mechanism_model_e1 with Transformers:
# Load model directly from transformers import AutoTokenizer, T5WithCopy tokenizer = AutoTokenizer.from_pretrained("bashyaldhiraj2067/copy_mechanism_model_e1") model = T5WithCopy.from_pretrained("bashyaldhiraj2067/copy_mechanism_model_e1") - Notebooks
- Google Colab
- Kaggle
copy_mechanism_model_e1
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.0575
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0651 | 0.3658 | 1000 | 4.0575 |
| 4.0586 | 0.7315 | 2000 | 4.0575 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
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