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---
datasets:
- pszemraj/scientific_lay_summarisation-plos-norm
language:
- en
metrics:
- bleu
- rouge
pipeline_tag: summarization
---
# Hyperparameters
learning_rate=2e-5
per_device_train_batch_size=14
per_device_eval_batch_size=14
weight_decay=0.01
save_total_limit=3
num_train_epochs=3
predict_with_generate=True
fp16=True
# Training Output
global_step=4248,
training_loss=2.4160910424988598,
metrics={'train_runtime': 14565.4519,
'train_samples_per_second': 4.082,
'train_steps_per_second': 0.292,
'total_flos': 1.7179021728232243e+17,
'train_loss': 2.4160910424988598,
'epoch': 3.0}
# Training Results
| Epoch | Training Loss | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|:----- |:------------ |:--------------- |:-------- | :------- |:-------- |:--------- |:-------- |:--------- |
|1| 2.467100| 2.303269| 0.410900| 0.136200| 0.235900| 0.235900| 0.465700| 182.332800
|2| 2.386700| 2.281062| 0.426300| 0.142300| 0.246800| 0.246700| 0.525200| 143.990900
|3| 2.362000| 2.274931| 0.428400| 0.143800| 0.248300| 0.248200| 0.532000| 139.585900 |