electra-small-touche-base-binary

This model is a fine-tuned version of google/electra-small-discriminator on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6289
Accuracy: 0.665
Macro F1: 0.6649
Fallacy F1: 0.6700

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: 3e-05
train_batch_size: 16
eval_batch_size: 64
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
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1	Fallacy F1
0.6951	1.0	47	0.6898	0.555	0.5094	0.3597
0.6876	2.0	94	0.6786	0.64	0.64	0.64
0.6429	3.0	141	0.6572	0.63	0.6161	0.5432
0.6258	4.0	188	0.6353	0.645	0.6430	0.6698
0.5856	5.0	235	0.6289	0.665	0.6649	0.6700

Framework versions

Transformers 5.9.0
Pytorch 2.11.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2

加载中…

heavyhelium/electra-small-touche-base-binary

electra-small-touche-base-binary

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

electra-small-touche-base-binary

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions