MTL-bert-base-uncased-ww

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: 2.5261

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
3.2964	1.0	99	2.9560
3.0419	2.0	198	2.8336
2.8979	3.0	297	2.8009
2.8815	4.0	396	2.7394
2.8373	5.0	495	2.6813
2.741	6.0	594	2.6270
2.6877	7.0	693	2.5216
2.6823	8.0	792	2.5485
2.6326	9.0	891	2.5690
2.5976	10.0	990	2.6336
2.6009	11.0	1089	2.5919
2.5615	12.0	1188	2.4264
2.5826	13.0	1287	2.5562
2.5693	14.0	1386	2.5529
2.5494	15.0	1485	2.5300

Framework versions

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