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---
datasets:
- multi_news
language:
- en
metrics:
- bleu
- rouge
library_name: transformers
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=7710,
training_loss=2.8554159399445727,
metrics={'train_runtime': 21924.7566,
'train_samples_per_second': 4.923,
'train_steps_per_second': 0.352,
'total_flos': 2.3807388210639667e+17,
'train_loss': 2.8554159399445727,
'epoch': 3.0}
# Training Results
| Epoch | Training Loss | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|:----- |:------------ |:--------------- |:-------- | :------- |:-------- |:--------- |:-------- |:--------- |
1| 2.981200| 2.831641| 0.414500| 0.147000| 0.230700| 0.230600| 0.512800| 140.734900|
2 |2.800900| 2.789402| 0.417300| 0.148400| 0.231800| 0.231700| 0.516000| 141.158200|
3 |2.680300| 2.780862| 0.418300| 0.148400| 0.232200| 0.232100| 0.516800| 140.872300| |