bart-large-cnn-samsum-ElectrifAi_v10

This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1748
Rouge1: 58.3392
Rouge2: 35.1686
Rougel: 45.4136
Rougelsum: 56.9138
Gen Len: 108.375

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	21	1.1573	56.0772	34.1572	44.3652	54.8621	106.0833
No log	2.0	42	1.1764	57.7245	34.6517	45.67	56.3426	106.4167
No log	3.0	63	1.1748	58.3392	35.1686	45.4136	56.9138	108.375

Framework versions

Transformers 4.25.1
Pytorch 1.12.1
Datasets 2.6.1
Tokenizers 0.13.2

作者:

Qiliang Huang

数据集大小:

1.52 GB