pegasus-pubmed-finetuned-paws
This model is a fine-tuned version of google/pegasus-pubmed on the paws dataset. It achieves the following results on the evaluation set:
- Loss: 3.5012
- Rouge1: 56.8108
- Rouge2: 36.2576
- Rougel: 51.1666
- Rougelsum: 51.2193
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 0.73 | 1000 | 3.8839 | 51.2731 | 29.8072 | 45.767 | 45.5732 |
| 4.071 | 1.47 | 2000 | 3.6459 | 52.756 | 31.9185 | 48.0092 | 48.0544 |
| 3.5467 | 2.2 | 3000 | 3.5849 | 54.8127 | 33.1959 | 49.326 | 49.4971 |
| 3.5467 | 2.93 | 4000 | 3.5267 | 55.387 | 33.9516 | 50.683 | 50.6313 |
| 3.3654 | 3.66 | 5000 | 3.5031 | 57.5279 | 35.2664 | 51.9903 | 52.258 |
| 3.2844 | 4.4 | 6000 | 3.5296 | 56.0536 | 33.395 | 50.9909 | 51.244 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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Dataset used to train domenicrosati/pegasus-pubmed-finetuned-paws
Evaluation results
- Rouge1 on pawsself-reported56.811
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("domenicrosati/pegasus-pubmed-finetuned-paws") model = AutoModelForSeq2SeqLM.from_pretrained("domenicrosati/pegasus-pubmed-finetuned-paws", device_map="auto")