armpln/modernbert-movie-reviews-polarity

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modernbert-movie-reviews-polarity

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

• —Loss: 0.3357
• —Accuracy: 0.9335

Model description

This model classifies movie reviews into:

• —negative
• —positive

• —Base model: answerdotai/ModernBERT-base
• —Task: Text Classification / Sentiment Analysis
• —Language: English
• —Labels: Binary polarity classification
• —Fine-tuned by: armpln
• —Framework: Transformers + PyTorch

Intended uses & limitations

This model can be used for:

• —Sentiment analysis of movie reviews
• —NLP educational experiments
• —Binary text classification demonstrations

Training and evaluation data

The model was fine-tuned on a dataset of English movie reviews labeled by sentiment polarity.

Classes:

• —0 = negative
• —1 = positive

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 5
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 5.7.0
• —Pytorch 2.10.0+cu128
• —Datasets 4.8.5
• —Tokenizers 0.22.2