This model is a fine-tuned version of
urduhack/roberta-urdu-small on the imdb_urdu_reviews dataset.
It achieves the following results on the evaluation set:
The model was fine-tuned using the transformers library and the Trainer class from Hugging Face. The training process involved the following steps:
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Tokenization: The input Urdu text was tokenized using the RobertaTokenizerFast from the "urduhack/roberta-urdu-small" pre-trained model. The texts were padded and truncated to a maximum length of 256 tokens.
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Model Architecture: The "urduhack/roberta-urdu-small" pre-trained model was loaded as the base model for sequence classification using the RobertaForSequenceClassification class.
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Training Arguments: The training arguments were set, including the number of training epochs, batch size, learning rate, evaluation strategy, logging strategy, and more.
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Training: The model was trained on the training dataset using the Trainer class. The training process was performed with gradient-based optimization techniques to minimize the cross-entropy loss between predicted and actual sentiment labels.
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Evaluation: After each epoch, the model was evaluated on the validation dataset to monitor its performance. The evaluation results, including training loss and validation loss, were logged for analysis.
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Fine-Tuning: The model parameters were fine-tuned during the training process to optimize its performance on the IMDb Urdu movie reviews sentiment analysis task.
The model was evaluated on an undisclosed dataset using a language modeling task. The evaluation results after 3 epochs of fine-tuning are as follows:
