postbot/MiniLMv2-L6-H384-mlm-multi-emails-hq

MiniLMv2-L6-H384-distilled-from-RoBERTa-Large-finetuned-wikitext103-mlm-multi-emails-hq-x2bs

This model is a fine-tuned version of saghar/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large-finetuned-wikitext103 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.0371
• Accuracy: 0.6450

Model description

• masked language model
• mini version of RoBERTa
• does support uppercase text

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: 0.0002
• train_batch_size: 16
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 16.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.2947	1.0	308	3.0832	0.5122
2.8727	2.0	616	2.6722	0.5662
2.6339	3.0	924	2.4797	0.5878
2.5053	4.0	1232	2.3833	0.6025
2.4531	5.0	1540	2.3085	0.6106
2.2852	6.0	1848	2.2451	0.6175
2.228	7.0	2156	2.1937	0.6244
2.2013	8.0	2464	2.1446	0.6310
2.1463	9.0	2772	2.1062	0.6357
2.0882	10.0	3080	2.0847	0.6370
2.1669	11.0	3388	2.0687	0.6399
2.0983	12.0	3696	2.0629	0.6423
2.1215	13.0	4004	2.0259	0.6476
2.1255	14.0	4312	2.0378	0.6461
2.1751	15.0	4620	2.0257	0.6458
1.9516	16.0	4928	2.0371	0.6450

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 2.0.0.dev20230212+cu118
• Datasets 2.9.0
• Tokenizers 0.13.2