gpt1_sst2_right

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gpt1_sst2_right

This model is a fine-tuned version of openai-gpt on sst2 dataset of GLUE benchmark. It achieves the following results on the evaluation set:

• Loss: 0.4216
• Accuracy: 0.9255
• Recall: 0.9369
• Precision: 0.9183

For testing, the model is loaded as a pipeline, and used for the prediction of each sample in test split. The samples and their predictions are recorded in test_preds.csv file. Access to Repository for finetuning.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

For batched training, <pad> token is added to the tokenizer and the following padding-truncation options are adapted:

• Padding Side: "right"
• Truncation Side: "right"

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 4

Training results

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0