jialicheng / ddi-biobert

huggingface.co
Total runs: 11
24-hour runs: 0
7-day runs: 4
30-day runs: 6
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

11
Total runs
0
24-hour runs
0
3-day runs
4
7-day runs
6
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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