clip-DIT-finetuned_one_text_to_train

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

• Loss: 1.3237

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: 1e-05
• train_batch_size: 64
• eval_batch_size: 100
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 200.0

Training results

Training Loss	Epoch	Step	Validation Loss
2.479	20.0	780	2.5238
0.5415	40.0	1560	1.9513
0.1937	60.0	2340	1.6752
0.1072	80.0	3120	1.5576
0.0722	100.0	3900	1.4878
0.0542	120.0	4680	1.4187
0.0433	140.0	5460	1.3938
0.0376	160.0	6240	1.3544
0.0333	180.0	7020	1.3325
0.0311	200.0	7800	1.3237

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1