This model is a fine-tuned version of pszemraj/random-mega-ar-small-4096 on the EleutherAI/wikitext_document_level dataset (wikitext-103-raw-v1). This model has ~ 65M params.

It achieves the following results on the evaluation set:

Loss: 4.0338
Accuracy: 0.3243

Training procedure

This was tuned with bf16, while the authors recommend tuning with fp32. Will try fp32 later.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 4
eval_batch_size: 1
seed: 80085
gradient_accumulation_steps: 32
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
7.3662	0.11	100	7.2782	0.0935
6.3064	0.22	200	6.2066	0.1634
5.8203	0.33	300	5.7299	0.1931
5.55	0.44	400	5.4173	0.2117
5.3194	0.55	500	5.1937	0.2278
5.1678	0.66	600	5.0206	0.2406
5.0375	0.77	700	4.8891	0.2508
4.9194	0.88	800	4.7592	0.2605
4.8272	0.99	900	4.6653	0.2681
4.7571	1.1	1000	4.5817	0.2754
4.6345	1.21	1100	4.5066	0.2820
4.6218	1.32	1200	4.4472	0.2867
4.5585	1.43	1300	4.3827	0.2923
4.5047	1.54	1400	4.3328	0.2963
4.4726	1.65	1500	4.2860	0.3002
4.4094	1.76	1600	4.2452	0.3038
4.3705	1.87	1700	4.2168	0.3062
4.3739	1.98	1800	4.1852	0.3095
4.2836	2.09	1900	4.1599	0.3112
4.302	2.2	2000	4.1307	0.3149
4.2847	2.31	2100	4.1113	0.3165
4.2348	2.42	2200	4.0925	0.3184
4.2837	2.53	2300	4.0743	0.3207
4.2058	2.64	2400	4.0612	0.3217
4.22	2.75	2500	4.0494	0.3224
4.1827	2.86	2600	4.0397	0.3237
4.1967	2.97	2700	4.0338	0.3243

Framework versions

Transformers 4.32.1
Pytorch 2.1.0.dev20230727+cu118
Datasets 2.13.1
Tokenizers 0.13.3

pszemraj/mega-ar-small-4096-wikitext-103-raw-v1

mega-ar-small-4096: MWE

mega-ar on wikitext-103-raw-v1 (document level)

Training procedure

Training hyperparameters

Training results

Framework versions

pszemraj/
mega-ar-small-4096-wikitext-103-raw-v1