jialicheng / ddi_biobert

huggingface.co
Total runs: 12
24-hour runs: -1
7-day runs: 2
30-day runs: 7
Model's Last Updated: December 27 2024
text-classification

Introduction of ddi_biobert

Model Details of ddi_biobert

biobert

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4906
  • Accuracy: 0.9444
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: 32
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
Training results
Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 791 0.2279 0.9384
0.1997 2.0 1582 0.3086 0.9326
0.0772 3.0 2373 0.3142 0.9305
0.0504 4.0 3164 0.3149 0.9417
0.0504 5.0 3955 0.3344 0.9414
0.0367 6.0 4746 0.3333 0.9430
0.0245 7.0 5537 0.3671 0.9409
0.0204 8.0 6328 0.4249 0.9395
0.0134 9.0 7119 0.3557 0.9456
0.0134 10.0 7910 0.4586 0.9384
0.0109 11.0 8701 0.5423 0.9374
0.0087 12.0 9492 0.4680 0.9458
0.0052 13.0 10283 0.4594 0.9458
0.0071 14.0 11074 0.5178 0.9389
0.0071 15.0 11865 0.4706 0.9421
0.0056 16.0 12656 0.4917 0.9435
0.0034 17.0 13447 0.4678 0.9447
0.0026 18.0 14238 0.4793 0.9447
0.0023 19.0 15029 0.4869 0.9458
0.0023 20.0 15820 0.4906 0.9444
Framework versions
  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2

Runs of jialicheng ddi_biobert on huggingface.co

12
Total runs
-1
24-hour runs
1
3-day runs
2
7-day runs
7
30-day runs

More Information About ddi_biobert huggingface.co Model

ddi_biobert huggingface.co

ddi_biobert huggingface.co is an AI model on huggingface.co that provides ddi_biobert's model effect (), which can be used instantly with this jialicheng ddi_biobert model. huggingface.co supports a free trial of the ddi_biobert model, and also provides paid use of the ddi_biobert. Support call ddi_biobert model through api, including Node.js, Python, http.

jialicheng ddi_biobert online free

ddi_biobert huggingface.co is an online trial and call api platform, which integrates ddi_biobert's modeling effects, including api services, and provides a free online trial of ddi_biobert, you can try ddi_biobert online for free by clicking the link below.

jialicheng ddi_biobert online free url in huggingface.co:

https://huggingface.co/jialicheng/ddi_biobert

ddi_biobert install

ddi_biobert is an open source model from GitHub that offers a free installation service, and any user can find ddi_biobert on GitHub to install. At the same time, huggingface.co provides the effect of ddi_biobert install, users can directly use ddi_biobert installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

ddi_biobert install url in huggingface.co:

https://huggingface.co/jialicheng/ddi_biobert

Url of ddi_biobert

Provider of ddi_biobert huggingface.co

jialicheng
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