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Bert-Sentiment-Fa

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metadata
library_name: transformers
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: Bert-Sentiment-Fa
    results: []

Bert-Sentiment-Fa

This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1484
  • Accuracy: 0.8417
  • F1: 0.8524

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: 3e-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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 68 0.5099 0.8042 0.8062
No log 2.0 136 0.6354 0.8083 0.8079
No log 3.0 204 0.6376 0.8458 0.8575
No log 4.0 272 0.8837 0.8292 0.8373
No log 5.0 340 0.9432 0.8167 0.8335
No log 6.0 408 0.9680 0.8125 0.8128
No log 7.0 476 0.8569 0.8292 0.8402
0.1247 8.0 544 1.0439 0.8542 0.8628
0.1247 9.0 612 1.0181 0.8375 0.8451
0.1247 10.0 680 1.0169 0.8458 0.8556
0.1247 11.0 748 1.1128 0.8292 0.8348
0.1247 12.0 816 1.1325 0.8333 0.8382
0.1247 13.0 884 1.1458 0.85 0.8622
0.1247 14.0 952 1.1439 0.85 0.8622
0.0062 15.0 1020 1.1484 0.8417 0.8524

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1