apwic / sentiment-base-2

huggingface.co
Total runs: 3
24-hour runs: 0
7-day runs: 2
30-day runs: 3
Model's Last Updated: June 03 2024

Introduction of sentiment-base-2

Model Details of sentiment-base-2

sentiment-base-2

This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8886
  • Accuracy: 0.8922
  • Precision: 0.8719
  • Recall: 0.8662
  • F1: 0.8690
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: 30
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0
Training results
Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.3808 1.0 122 0.3794 0.8647 0.8737 0.7917 0.8186
0.221 2.0 244 0.2851 0.8722 0.8562 0.8271 0.8395
0.1363 3.0 366 0.3832 0.8947 0.8757 0.8680 0.8717
0.099 4.0 488 0.4968 0.8972 0.8869 0.8598 0.8717
0.0702 5.0 610 0.5205 0.8697 0.8503 0.8278 0.8377
0.0469 6.0 732 0.5740 0.8747 0.8552 0.8363 0.8448
0.0328 7.0 854 0.6012 0.8847 0.8581 0.8684 0.8629
0.0284 8.0 976 0.5403 0.8972 0.8812 0.8673 0.8738
0.019 9.0 1098 0.5909 0.8922 0.8657 0.8813 0.8728
0.016 10.0 1220 0.8931 0.8822 0.8694 0.8392 0.8521
0.0167 11.0 1342 0.6618 0.8972 0.8781 0.8723 0.8751
0.0168 12.0 1464 0.7513 0.9023 0.8842 0.8783 0.8812
0.0064 13.0 1586 0.7513 0.8997 0.8819 0.8741 0.8778
0.0078 14.0 1708 0.8152 0.8947 0.8789 0.8630 0.8704
0.0064 15.0 1830 0.7460 0.8997 0.8778 0.8816 0.8797
0.0055 16.0 1952 0.8232 0.8922 0.8734 0.8637 0.8683
0.006 17.0 2074 0.8421 0.8947 0.8757 0.8680 0.8717
0.0052 18.0 2196 0.8442 0.8872 0.8624 0.8677 0.8650
0.0035 19.0 2318 0.8841 0.8897 0.8682 0.8645 0.8663
0.0013 20.0 2440 0.8886 0.8922 0.8719 0.8662 0.8690
Framework versions
  • Transformers 4.39.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.15.2

Runs of apwic sentiment-base-2 on huggingface.co

3
Total runs
0
24-hour runs
0
3-day runs
2
7-day runs
3
30-day runs

More Information About sentiment-base-2 huggingface.co Model

More sentiment-base-2 license Visit here:

https://choosealicense.com/licenses/mit

sentiment-base-2 huggingface.co

sentiment-base-2 huggingface.co is an AI model on huggingface.co that provides sentiment-base-2's model effect (), which can be used instantly with this apwic sentiment-base-2 model. huggingface.co supports a free trial of the sentiment-base-2 model, and also provides paid use of the sentiment-base-2. Support call sentiment-base-2 model through api, including Node.js, Python, http.

sentiment-base-2 huggingface.co Url

https://huggingface.co/apwic/sentiment-base-2

apwic sentiment-base-2 online free

sentiment-base-2 huggingface.co is an online trial and call api platform, which integrates sentiment-base-2's modeling effects, including api services, and provides a free online trial of sentiment-base-2, you can try sentiment-base-2 online for free by clicking the link below.

apwic sentiment-base-2 online free url in huggingface.co:

https://huggingface.co/apwic/sentiment-base-2

sentiment-base-2 install

sentiment-base-2 is an open source model from GitHub that offers a free installation service, and any user can find sentiment-base-2 on GitHub to install. At the same time, huggingface.co provides the effect of sentiment-base-2 install, users can directly use sentiment-base-2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

sentiment-base-2 install url in huggingface.co:

https://huggingface.co/apwic/sentiment-base-2

Url of sentiment-base-2

sentiment-base-2 huggingface.co Url

Provider of sentiment-base-2 huggingface.co

apwic
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