metadata
tags:
- generated_from_trainer
- summarize
- pubmed
- med
datasets:
- pubmed-summarization
metrics:
- rouge
model-index:
- name: fine-tuned-16384-pubmed
results: []
language:
- en
fine-tuned-16384-pubmed
This model is fine-tuned on the pubmed-summarization dataset. It achieves the following results on the evaluation set:
- Loss: 0.3719
- Rouge1: 0.4602
- Rouge2: 0.2253
- Rougel: 0.2911
- Rougelsum: 0.4283
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 12.7776 | 0.2667 | 50 | 9.5450 | 0.4552 | 0.2219 | 0.2848 | 0.4234 |
| 7.2062 | 0.5333 | 100 | 4.6159 | 0.4564 | 0.2215 | 0.2874 | 0.4241 |
| 4.0511 | 0.8 | 150 | 2.7224 | 0.4615 | 0.2222 | 0.2914 | 0.4287 |
| 2.657 | 1.0667 | 200 | 1.7347 | 0.4597 | 0.2226 | 0.2921 | 0.4273 |
| 1.7104 | 1.3333 | 250 | 1.0021 | 0.4583 | 0.2231 | 0.2918 | 0.4261 |
| 0.9336 | 1.6 | 300 | 0.5423 | 0.4586 | 0.2228 | 0.2905 | 0.4259 |
| 0.4902 | 1.8667 | 350 | 0.3719 | 0.4602 | 0.2253 | 0.2911 | 0.4283 |
| 0.4032 | 2 | 400 | 0.2967 | 0.4718 | 0.2203 | 0.2871 | 0.4243 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.19.1