---
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