---
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|