pythia-31m-KI_v1-2048-scratch

Initialized from random weights based on config of EleutherAI/pythia-31m, 3 epochs bf16 It achieves the following results on the evaluation set:

• Loss: 4.6160
• Accuracy: 0.2448

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: 0.0005
• train_batch_size: 2
• eval_batch_size: 2
• seed: 80085
• gradient_accumulation_steps: 64
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
• lr_scheduler_type: inverse_sqrt
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.3874	0.16	100	6.4212	0.1487
5.7088	0.32	200	5.7926	0.1725
5.4575	0.48	300	5.5160	0.1903
5.2451	0.64	400	5.3429	0.1995
5.0954	0.8	500	5.2109	0.2059
5.0358	0.96	600	5.1068	0.2123
4.94	1.12	700	5.0321	0.2157
4.8532	1.28	800	4.9605	0.2202
4.7602	1.44	900	4.9047	0.224
4.6965	1.6	1000	4.8526	0.2276
4.6855	1.76	1100	4.8139	0.2300
4.6573	1.91	1200	4.7739	0.2327
4.5968	2.07	1300	4.7451	0.2346
4.5688	2.23	1400	4.7152	0.2370
4.5205	2.39	1500	4.6842	0.2396
4.5369	2.55	1600	4.6598	0.2410
4.5106	2.71	1700	4.6352	0.2433
4.4375	2.87	1800	4.6160	0.2448

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	25.21
ARC (25-shot)	23.12
HellaSwag (10-shot)	25.23
MMLU (5-shot)	23.12
TruthfulQA (0-shot)	51.67
Winogrande (5-shot)	51.78
GSM8K (5-shot)	0.0
DROP (3-shot)	1.52