davanstrien / demo

huggingface.co
Total runs: 4
24-hour runs: 0
7-day runs: 1
30-day runs: 3
Model's Last Updated: July 25 2023
text-classification

Introduction of demo

Model Details of demo

demo

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1142
  • Accuracy: 0.9703
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: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.1484 1.0 2206 0.1221 0.9629
0.0962 2.0 4412 0.1142 0.9703
Framework versions
  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.0
  • Tokenizers 0.13.3

Runs of davanstrien demo on huggingface.co

4
Total runs
0
24-hour runs
0
3-day runs
1
7-day runs
3
30-day runs

More Information About demo huggingface.co Model

More demo license Visit here:

https://choosealicense.com/licenses/mit

demo huggingface.co

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

davanstrien demo online free

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

davanstrien demo online free url in huggingface.co:

https://huggingface.co/davanstrien/demo

demo install

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

demo install url in huggingface.co:

https://huggingface.co/davanstrien/demo

Url of demo

Provider of demo huggingface.co

davanstrien
ORGANIZATIONS

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