Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use vishnun/HintsGenerator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishnun/HintsGenerator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vishnun/HintsGenerator") model = AutoModelForSeq2SeqLM.from_pretrained("vishnun/HintsGenerator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: HintsGenerator | |
| results: [] | |
| <!-- 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. --> | |
| # HintsGenerator | |
| This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.7541 | |
| ## 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: 64 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 10 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:-----:|:---------------:| | |
| | 2.2228 | 1.0 | 1053 | 1.8560 | | |
| | 2.078 | 2.0 | 2106 | 1.7876 | | |
| | 1.9936 | 3.0 | 3159 | 1.7681 | | |
| | 1.9479 | 4.0 | 4212 | 1.7580 | | |
| | 1.911 | 5.0 | 5265 | 1.7552 | | |
| | 1.883 | 6.0 | 6318 | 1.7642 | | |
| | 1.8738 | 7.0 | 7371 | 1.7618 | | |
| | 1.8524 | 8.0 | 8424 | 1.7571 | | |
| | 1.847 | 9.0 | 9477 | 1.7532 | | |
| | 1.8346 | 10.0 | 10530 | 1.7541 | | |
| ### Framework versions | |
| - Transformers 4.30.1 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |