MTL-distilbert-base-uncased

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: 2.0874

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: 7
• eval_batch_size: 7
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.5593	1.0	99	2.3163
2.4346	2.0	198	2.2918
2.3377	3.0	297	2.2345
2.2953	4.0	396	2.1463
2.2296	5.0	495	2.1761
2.2235	6.0	594	2.0721
2.1878	7.0	693	2.1460
2.1569	8.0	792	2.0856
2.1455	9.0	891	2.1039
2.1391	10.0	990	2.1112
2.1056	11.0	1089	2.0694
2.1076	12.0	1188	2.0501
2.0919	13.0	1287	2.0484
2.0669	14.0	1386	2.0342
2.0595	15.0	1485	2.0802

Framework versions

• Transformers 4.16.2
• Pytorch 1.10.0+cu111
• Datasets 1.18.3
• Tokenizers 0.11.0