MTL-bert-base-uncased

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

• Loss: 1.9283

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
2.4409	1.0	99	2.1982
2.2905	2.0	198	2.1643
2.1974	3.0	297	2.1168
2.15	4.0	396	2.0023
2.0823	5.0	495	2.0199
2.0752	6.0	594	1.9061
2.0408	7.0	693	1.9770
1.9984	8.0	792	1.9322
1.9933	9.0	891	1.9167
1.9806	10.0	990	1.9652
1.9436	11.0	1089	1.9308
1.9491	12.0	1188	1.9064
1.929	13.0	1287	1.8831
1.9096	14.0	1386	1.8927
1.9032	15.0	1485	1.9117

Framework versions

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