| --- |
| license: apache-2.0 |
| --- |
| # YusufDagdeviren/SentimentAnalysisFromMovieReviews |
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| This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the imdb dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.16 |
| - Accuracy: 0.93 |
| - F1: 0.93 |
|
|
| ## Model Description |
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| This project uses a fine-tuned XLNet model for sentiment analysis on English movie reviews. The model was fine-tuned using PyTorch and Huggingface Transformers libraries to improve its performance on sentiment classification tasks. |
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| XLNet (eXtreme Language Model) is an autoregressive pre-training method that combines the best of BERT and Transformer-XL architectures, providing significant improvements in performance over traditional language models. This fine-tuned XLNet model aims to provide high accuracy and reliability in sentiment analysis. |
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| The training process involved the use of the AdamW optimizer with a learning rate of 2e-5, betas of [0.9, 0.999], and epsilon of 1e-6. The model was trained for 2 epochs with a linear learning rate scheduler and no warmup steps. |
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| ## Training and Evaluation Data |
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| [IMDB Dataset of 50K Movie Reviews](https://www.kaggle.com/datasets/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews) |
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|
| ### Training Hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 2e-5 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - total_train_batch_size: 38 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-6 |
| - lr_scheduler_type: linear |
| - num_epochs: 2 |
| ### Training Results |
| |
| ======== Epoch 1 / 2 ======== |
| Training... |
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| Average training loss: 0.27 |
| Training epoch took: 0:25:12 |
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| Running Validation... |
| Accuracy: 0.92 |
| Validation took: 0:02:51 |
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| ======== Epoch 2 / 2 ======== |
| Training... |
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| Average training loss: 0.16 |
| Training epoch took: 0:25:12 |
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| Running Validation... |
| Accuracy: 0.93 |
| Validation took: 0:02:52 |
| |
| ### Framework Versions |
| - Transformers 4.41.2 |
| - Pytorch 2.3 |
| - Tokenizers 0.19.1 |
