Comment_Score_By_douban_-finetuned-financial_data

This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8968
• Mse: 0.8968
• Rmse: 0.9470
• Mae: 0.7104
• R2: 0.4941
• Smape: 24.0094

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: 128
• eval_batch_size: 20
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Rmse	Mae	R2	Smape
No log	1.0	169	0.8968	0.8968	0.9470	0.7104	0.4941	24.0094
No log	2.0	338	0.6792	0.6792	0.8241	0.6188	0.6169	21.1323
0.8399	3.0	507	0.6845	0.6845	0.8274	0.6031	0.6138	20.6587
0.8399	4.0	676	0.6598	0.6598	0.8123	0.5881	0.6278	20.1132
0.8399	5.0	845	0.6820	0.6820	0.8258	0.5909	0.6153	20.1342

Framework versions

• Transformers 4.26.0
• Pytorch 1.12.1+cu113
• Datasets 2.9.0
• Tokenizers 0.13.2