empathy_classifier

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0540
• Mse: 0.0540
• Mae: 0.1938
• Pearson: 0.4722

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 64
• 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: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	Pearson
No log	1.0	47	0.0662	0.0662	0.2175	0.3286
No log	2.0	94	0.0560	0.0560	0.1993	0.4229
No log	3.0	141	0.0538	0.0538	0.1944	0.4611
No log	4.0	188	0.0601	0.0601	0.2036	0.4580
No log	5.0	235	0.0540	0.0540	0.1938	0.4722
No log	6.0	282	0.0542	0.0542	0.1942	0.4720

Framework versions

• Transformers 4.46.2
• Pytorch 2.6.0+cu124
• Datasets 3.3.2
• Tokenizers 0.20.3