distilbert-finetuned-mrr – AI Model by limhayi | AlphaNeural AI

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limhayi/
distilbert-finetuned-mrr

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distilbert/distilbert-base-uncased

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distilbert-finetuned-mrr

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: 2.5354

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: 8
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss
2.7969	1.0	151	2.7004
2.7110	2.0	302	2.5984
2.6611	3.0	453	2.5624
2.6357	4.0	604	2.5794
2.6175	5.0	755	2.5713
2.5854	6.0	906	2.5350
2.5872	7.0	1057	2.5060
2.5351	8.0	1208	2.5180
2.5459	9.0	1359	2.5456
2.5591	10.0	1510	2.5354

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2