sequence_classification_learn

This model is trained following this tutorial: https://huggingface.co/docs/transformers/tasks/sequence_classification. Since it is for study purpose, the performance is not garanteed (It is only trained for 2 epochs).This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2325
• Accuracy: 0.9323

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2232	1.0	1563	0.2204	0.9156
0.1479	2.0	3126	0.2325	0.9323

Framework versions

• Transformers 4.53.1
• Pytorch 2.6.0+cu124
• Datasets 4.0.0
• Tokenizers 0.21.2