enlm-roberta-final

This model is a fine-tuned version of manirai91/enlm-roberta on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4187

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: 6e-06
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 128
• total_train_batch_size: 8192
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
• lr_scheduler_type: polynomial
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
1.5245	0.34	160	1.4187
1.5245	0.69	320	1.4183
1.5259	1.03	480	1.4177
1.5265	1.37	640	1.4185
1.5245	1.72	800	1.4190
1.5241	2.06	960	1.4172
1.5227	2.4	1120	1.4165
1.5226	2.75	1280	1.4152
1.522	3.09	1440	1.4190
1.5243	3.43	1600	1.4177
1.5213	3.78	1760	1.4134
1.524	4.12	1920	1.4140
1.5223	4.46	2080	1.4173
1.5236	4.81	2240	1.4121
1.5239	5.15	2400	1.4186
1.5203	5.49	2560	1.4154
1.522	5.84	2720	1.4162
1.5209	6.18	2880	1.4154
1.5196	6.52	3040	1.4153
1.5209	6.87	3200	1.4122
1.5202	7.21	3360	1.4146
1.5192	7.55	3520	1.4141
1.5215	7.9	3680	1.4123
1.5228	8.24	3840	1.4147
1.5222	8.58	4000	1.4144
1.5201	8.93	4160	1.4173
1.523	9.27	4320	1.4171
1.5212	9.61	4480	1.4149
1.522	9.96	4640	1.4187

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0
• Datasets 2.3.2
• Tokenizers 0.12.1