distilbert_add_GLUE_Experiment_cola_256

This model is a fine-tuned version of distilbert-base-uncased on the GLUE COLA dataset. It achieves the following results on the evaluation set:

• Loss: 0.6181
• Matthews Correlation: 0.0

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: 5e-05
• train_batch_size: 256
• eval_batch_size: 256
• seed: 10
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.6125	1.0	34	0.6201	0.0
0.6084	2.0	68	0.6182	0.0
0.6071	3.0	102	0.6184	0.0
0.6081	4.0	136	0.6186	0.0
0.6081	5.0	170	0.6182	0.0
0.607	6.0	204	0.6185	0.0
0.6082	7.0	238	0.6181	0.0
0.609	8.0	272	0.6184	0.0
0.607	9.0	306	0.6213	0.0
0.6082	10.0	340	0.6193	0.0
0.6081	11.0	374	0.6196	0.0
0.6071	12.0	408	0.6193	0.0

Framework versions

• Transformers 4.26.0
• Pytorch 1.14.0a0+410ce96
• Datasets 2.8.0
• Tokenizers 0.13.2