distilbert-base-uncased-finetunned-elementos-contractuales

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.0947
• Accuracy: 0.8398
• F1: 0.8564

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	39	0.9113	0.8356	0.8527
No log	2.0	78	1.0381	0.8339	0.8527
No log	3.0	117	0.9843	0.8297	0.8490
No log	4.0	156	1.0604	0.8381	0.8554
No log	5.0	195	1.0013	0.8424	0.8582
No log	6.0	234	1.0472	0.8398	0.8567
No log	7.0	273	1.1018	0.8364	0.8543
No log	8.0	312	1.0839	0.8381	0.8554
No log	9.0	351	1.0961	0.8381	0.8553
No log	10.0	390	1.0947	0.8398	0.8564

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1