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---
datasets:
- multi_news
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=7710,
training_loss=2.436398018566087,
metrics={'train_runtime': 30287.1254,
'train_samples_per_second': 3.564,
'train_steps_per_second': 0.255,
'total_flos': 3.1186278368988365e+17,
'train_loss': 2.436398018566087,
'epoch': 3.0}
# Training Results
| Epoch | Training Loss | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|:----- |:------------ |:--------------- |:-------- | :------- |:-------- |:--------- |:-------- |:--------- |
1| 2.451200| 2.291708| 0.322800| 0.110100| 0.194600| 0.194700| 0.368400| 150.224300
2| 2.527300| nan| 0.296400| 0.100100| 0.181800| 0.181900 |0.317300| 137.569200
3| 2.523800| nan |0.296600| 0.100000| 0.181800 |0.181900 |0.317200| 137.254000 |