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hw2942/
Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1

Name: Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1

This model is a fine-tuned version of IDEA-CCNL/Erlangshen-Longformer-330M on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6971
Accuracy: 0.5

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	150	0.7366	0.5
No log	2.0	300	0.7063	0.5
No log	3.0	450	0.6971	0.5
0.7857	4.0	600	0.6971	0.5
0.7857	5.0	750	0.6971	0.5
0.7857	6.0	900	0.6971	0.5
0.696	7.0	1050	0.6971	0.5
0.696	8.0	1200	0.6971	0.5
0.696	9.0	1350	0.6971	0.5
0.6916	10.0	1500	0.6971	0.5

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

hw2942/Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1

Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hw2942/
Erlangshen-Longformer-330M-finetuning-wallstreetcn-morning-news-vix-sz50-1