tfm-distilbert-sesgo

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.9827
• Accuracy: 0.25
• Macro F1: 0.2375

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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
No log	1.0	7	2.0647	0.2083	0.1146
No log	2.0	14	2.0509	0.2083	0.1042
No log	3.0	21	2.0327	0.25	0.1540
No log	4.0	28	2.0160	0.25	0.2087
No log	5.0	35	2.0035	0.25	0.2138
No log	6.0	42	1.9921	0.2083	0.1690
No log	7.0	49	1.9854	0.25	0.2375
No log	8.0	56	1.9827	0.25	0.2375

Framework versions

• Transformers 5.8.1
• Pytorch 2.10.0+cu128
• Datasets 4.8.5
• Tokenizers 0.22.2