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Verified signature# DistilBERT Sentiment Analysis Model ## Overview This repository contains a fine-tuned **DistilBERT** model trained for sentiment analysis on TripAdvisor reviews. The model predicts sentiment scores on a scale of 1 to 5 based on review text. - **Base Model**: `distilbert-base-uncased` - **Trained Dataset**: [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets/nhull/tripadvisor-split-dataset-v2) - **Use Case**: Sentiment classification for customer reviews to derive insights into customer satisfaction. - **Output**: Sentiment labels (1-5). --- ## Model Details - **Learning Rate**: `3e-05` - **Batch Size**: `64` - **Epochs**: `10` (with early stopping) - **Patience**: `5` (epochs without improvement) - **Tokenizer**: `distilbert-base-uncased` - **Framework**: PyTorch + Hugging Face Transformers --- ## Training and Validation ### Dataset The dataset used for training, validation, and testing is [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets…1a334dc -
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Verified signature# DistilBERT Sentiment Analysis Model ## Overview This repository contains a fine-tuned **DistilBERT** model trained for sentiment analysis on TripAdvisor reviews. The model predicts sentiment scores on a scale of 1 to 5 based on review text. - **Base Model**: `distilbert-base-uncased` - **Trained Dataset**: [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets/nhull/tripadvisor-split-dataset-v2) - **Use Case**: Sentiment classification for customer reviews to derive insights into customer satisfaction. - **Output**: Sentiment labels (1-5). --- ## Model Details - **Learning Rate**: `3e-05` - **Batch Size**: `64` - **Epochs**: `10` (with early stopping) - **Patience**: `5` (epochs without improvement) - **Tokenizer**: `distilbert-base-uncased` - **Framework**: PyTorch + Hugging Face Transformers --- ## Training and Validation ### Dataset The dataset used for training, validation, and testing is [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets…61f1855 -
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Verified signature# DistilBERT Sentiment Analysis Model ## Overview This repository contains a fine-tuned **DistilBERT** model trained for sentiment analysis on TripAdvisor reviews. The model predicts sentiment scores on a scale of 1 to 5 based on review text. - **Base Model**: `distilbert-base-uncased` - **Trained Dataset**: [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets/nhull/tripadvisor-split-dataset-v2) - **Use Case**: Sentiment classification for customer reviews to derive insights into customer satisfaction. - **Output**: Sentiment labels (1-5). --- ## Model Details - **Learning Rate**: `3e-05` - **Batch Size**: `64` - **Epochs**: `10` (with early stopping) - **Patience**: `5` (epochs without improvement) - **Tokenizer**: `distilbert-base-uncased` - **Framework**: PyTorch + Hugging Face Transformers --- ## Training and Validation ### Dataset The dataset used for training, validation, and testing is [nhull/tripadvisor-split-dataset-v2](https://huggingface.co/datasets…222e461 -
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