RogerB / deberta-base-finetuned-kintweetsE

huggingface.co
Total runs: 9
24-hour runs: 2
7-day runs: 3
30-day runs: 5
Model's Last Updated: July 10 2023
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Introduction of deberta-base-finetuned-kintweetsE

Model Details of deberta-base-finetuned-kintweetsE

deberta-base-finetuned-kintweetsE

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

  • Loss: 3.4010
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: 10
  • eval_batch_size: 10
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0
Training results
Training Loss Epoch Step Validation Loss
4.7396 1.0 1000 3.9160
3.7652 2.0 2000 3.4778
3.5318 3.0 3000 3.3727
Framework versions
  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of RogerB deberta-base-finetuned-kintweetsE on huggingface.co

9
Total runs
2
24-hour runs
2
3-day runs
3
7-day runs
5
30-day runs

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deberta-base-finetuned-kintweetsE install

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

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