Instructions to use zwellington/clu-pubhealth-base-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zwellington/clu-pubhealth-base-3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zwellington/clu-pubhealth-base-3") model = AutoModelForSeq2SeqLM.from_pretrained("zwellington/clu-pubhealth-base-3") - Notebooks
- Google Colab
- Kaggle
clu-pubhealth-base-3
This model is a fine-tuned version of facebook/bart-base on the clupubhealth dataset. It achieves the following results on the evaluation set:
- Loss: 2.2514
- Rouge1: 28.0559
- Rouge2: 9.0287
- Rougel: 22.2344
- Rougelsum: 22.4603
- Gen Len: 19.695
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: 4
- seed: 42
- gradient_accumulation_steps: 20
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.2512 | 0.63 | 20 | 2.2514 | 28.0559 | 9.0287 | 22.2344 | 22.4603 | 19.695 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
- Downloads last month
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Model tree for zwellington/clu-pubhealth-base-3
Base model
facebook/bart-baseEvaluation results
- Rouge1 on clupubhealthtest set self-reported28.056