Summarization
Transformers
PyTorch
TensorBoard
bart
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use cs608/billsum-model-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cs608/billsum-model-2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="cs608/billsum-model-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cs608/billsum-model-2") model = AutoModelForSeq2SeqLM.from_pretrained("cs608/billsum-model-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from cs608/billsum-model-2: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
-
https://huggingface.co/cs608/billsum-model-2/resolve/main/README.md
- Command line
-
hf download hf://cs608/billsum-model-2/README.md
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curl -L -o README.md https://huggingface.co/cs608/billsum-model-2/resolve/main/README.md
2.18 kB
| license: apache-2.0 | |
| tags: | |
| - summarization | |
| - generated_from_trainer | |
| datasets: | |
| - billsum | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: CS685-text-summarizer-2 | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: billsum | |
| type: billsum | |
| config: default | |
| split: train[:37%] | |
| args: default | |
| metrics: | |
| - name: Rouge1 | |
| type: rouge | |
| value: 17.4066 | |
| <!-- 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. --> | |
| # CS685-text-summarizer-2 | |
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the billsum dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.7516 | |
| - Rouge1: 17.4066 | |
| - Rouge2: 14.022 | |
| - Rougel: 16.9378 | |
| - Rougelsum: 17.0519 | |
| ## 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: 5.6e-05 | |
| - train_batch_size: 6 | |
| - eval_batch_size: 6 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| | |
| | 2.3529 | 1.0 | 1052 | 1.9277 | 17.1288 | 13.5932 | 16.6346 | 16.7728 | | |
| | 1.9686 | 2.0 | 2104 | 1.8297 | 17.2756 | 13.7685 | 16.7924 | 16.9242 | | |
| | 1.789 | 3.0 | 3156 | 1.7903 | 17.4219 | 14.0205 | 16.9082 | 17.0564 | | |
| | 1.6619 | 4.0 | 4208 | 1.7632 | 17.5055 | 14.1186 | 16.996 | 17.1265 | | |
| | 1.5819 | 5.0 | 5260 | 1.7516 | 17.4066 | 14.022 | 16.9378 | 17.0519 | | |
| ### Framework versions | |
| - Transformers 4.28.0 | |
| - Pytorch 2.0.0+cu118 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |