README.md

metadata

tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: HsscBERT_abs_and_full
    results: []

HsscBERT_abs_and_full

This model is a fine-tuned version of /home/hscrc/pretrained_models/bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6037
• Accuracy: 0.8504

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: 32
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 9
• total_train_batch_size: 288
• total_eval_batch_size: 144
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.8163	0.19	5000	0.8326	0.6971
0.7942	0.38	10000	0.8364	0.6761
0.7817	0.57	15000	0.8384	0.6651
0.7751	0.75	20000	0.8402	0.6563
0.7654	0.94	25000	0.8415	0.6490
0.7546	1.13	30000	0.8427	0.6441
0.7527	1.32	35000	0.8434	0.6398
0.7484	1.51	40000	0.8444	0.6345
0.7443	1.7	45000	0.8450	0.6318
0.74	1.88	50000	0.8456	0.6292
0.738	2.07	55000	0.8460	0.6268
0.734	2.26	60000	0.8464	0.6246
0.7335	2.45	65000	0.8467	0.6229
0.7299	2.64	70000	0.8470	0.6212
0.7291	2.83	75000	0.8473	0.6201

Framework versions

• Transformers 4.26.1
• Pytorch 1.10.0+cu113
• Datasets 2.9.0
• Tokenizers 0.13.2