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metadata
license: apache-2.0
base_model: dadashzadeh/tiny-bert-Sentiment-persian
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: tiny-bert-Sentiment-persian
    results: []
datasets:
  - hezarai/sentiment-dksf
language:
  - fa
pipeline_tag: text-classification

tiny-bert-Sentiment-persian

This model is a fine-tuned version of dadashzadeh/tiny-bert-Sentiment-persian on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6553
  • Accuracy: 0.7611

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: 2
  • eval_batch_size: 2
  • seed: 45
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6157 0.9999 3575 0.6703 0.7577
0.5833 1.9999 7150 0.7599 0.7171
0.6015 2.9998 10725 0.6824 0.7590
0.5601 4.0 14301 0.6780 0.7533
0.5699 4.9999 17876 0.7071 0.7356
0.5519 5.9999 21451 0.6931 0.7391
0.5436 6.9998 25026 0.6736 0.7629
0.5482 8.0 28602 0.6567 0.7685
0.5367 8.9999 32177 0.6553 0.7611
0.5399 9.9999 35752 0.6691 0.7616
0.5112 10.9998 39327 0.6785 0.7564
0.5113 11.9992 42900 0.6773 0.7572

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.2+cu118
  • Datasets 2.19.1
  • Tokenizers 0.19.1