menesnas/fine-tuned-gpt2-tweet-sentiment

Model Card for Model ID

This is a fine-tuned GPT-2 model for tweet sentiment classification. It categorizes tweets into positive, neutral, or negative sentiment based on their content.

Model Description

• Model type: GPT-2 (with sequence classification head)
• Language(s) (NLP): English
• License: MIT
• Finetuned from model [optional]: gpt2

Metrics

The model was evaluated using the following metrics:

• Training Loss: Measures how well the model fits the training data. A lower value indicates better learning.

• Validation Loss: Measures how well the model generalizes to unseen data. It is used to detect overfitting.

• Accuracy: Percentage of correctly classified samples in the validation dataset. It is the primary performance metric for this sentiment classification task.

Results

• The model was trained for 3 epochs. Below are the results per epoch:

• Epoch	Training Loss	Validation Loss	Accuracy
  1	0.832400	0.871651	62.7%
  2	0.512700	0.794255	69.3%
  3	0.517500	0.819540	71.8%