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---
datasets:
- pszemraj/scientific_lay_summarisation-plos-norm
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=2.930363613782405,
metrics={'train_runtime': 11857.8062,
'train_samples_per_second': 5.014,
'train_steps_per_second': 0.358,
'total_flos': 1.3114345819786445e+17,
'train_loss': 2.930363613782405,
'epoch': 3.0}
# Training Results
Epoch| Training Loss| Validation Loss| Rouge1| Rouge2| Rougel| Rougelsum| Bleu| Gen Len|
|:----- |:------------ |:--------------- |:-------- | :------- |:-------- |:--------- |:-------- |:--------- |
1| 3.095400| 2.864138| 0.425500| 0.139000| 0.246300| 0.246300| 0.541400| 141.540900|
2| 2.876500| 2.811244| 0.425600| 0.139100| 0.246500| 0.246400| 0.541600| 141.619000|
3| 2.748300| 2.797923| 0.425800| 0.138700| 0.246400| 0.246300| 0.541800| 141.597000| |