Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use chunwoolee0/ke_t5_small_nikl_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chunwoolee0/ke_t5_small_nikl_summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("chunwoolee0/ke_t5_small_nikl_summarization") model = AutoModelForMultimodalLM.from_pretrained("chunwoolee0/ke_t5_small_nikl_summarization") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: KETI-AIR/ke-t5-small | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - summary_and_report | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: ke_t5_small_nikl_summarization | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: summary_and_report | |
| type: summary_and_report | |
| config: base | |
| split: train | |
| args: base | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 0.0 | |
| <!-- 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. --> | |
| # ke_t5_small_nikl_summarization | |
| This model is a fine-tuned version of [KETI-AIR/ke-t5-small](https://huggingface.co/KETI-AIR/ke-t5-small) on the summary_and_report dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: nan | |
| - Rouge1: 0.0 | |
| - Rouge2: 0.0 | |
| - Rougel: 0.0 | |
| - Rougelsum: 0.0 | |
| - Gen Len: 0.0 | |
| ## 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: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | |
| | 0.0 | 1.0 | 4594 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | | |
| | 0.0 | 2.0 | 9188 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | | |
| | 0.0 | 3.0 | 13782 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | | |
| ### Framework versions | |
| - Transformers 4.33.2 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.13.3 | |