pythia-31m-simplepile-lite-2048-scratch-2e – AI Model by pszemraj | AlphaNeural AI

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pszemraj/
pythia-31m-simplepile-lite-2048-scratch-2e

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text-generation

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pszemraj/simplepile-lite

autotrain_compatible

text-generation-inference

endpoints_compatible

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BL-pythia-31m-simplepile-lite-2048-scratch

Train from scratch based on config of EleutherAI/pythia-31m on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.9891
Accuracy: 0.3498

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: 1
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: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
7.4089	0.07	100	7.3885	0.1133
6.2774	0.13	200	6.2091	0.1621
5.7019	0.2	300	5.7450	0.1890
5.4922	0.27	400	5.4697	0.2080
5.233	0.33	500	5.2846	0.2195
5.0523	0.4	600	5.1479	0.2296
4.9396	0.47	700	5.0391	0.2376
4.7633	0.53	800	4.9366	0.2458
4.7516	0.6	900	4.8339	0.2559
4.5937	0.67	1000	4.7286	0.2676
4.5079	0.73	1100	4.6293	0.2798
4.4608	0.8	1200	4.5433	0.2903
4.3426	0.87	1300	4.4719	0.2988
4.1722	0.93	1400	4.4089	0.3057
4.1655	1.0	1500	4.3585	0.3107
4.0927	1.07	1600	4.3101	0.3161
4.1439	1.13	1700	4.2714	0.3206
4.0064	1.2	1800	4.2330	0.3249
4.0633	1.27	1900	4.2015	0.3281
3.9948	1.33	2000	4.1702	0.3311
3.9389	1.4	2100	4.1439	0.3338
3.8833	1.47	2200	4.1200	0.3367
3.8411	1.53	2300	4.0949	0.3395
3.8481	1.6	2400	4.0764	0.3408
3.8397	1.67	2500	4.0578	0.3420
3.8897	1.73	2600	4.0383	0.3440
3.8785	1.8	2700	4.0206	0.3459
3.8126	1.87	2800	4.0044	0.3478
3.783	1.93	2900	3.9891	0.3498

Framework versions

Transformers 4.33.1
Pytorch 2.2.0.dev20230907+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.7
ARC (25-shot)	21.59
HellaSwag (10-shot)	25.79
MMLU (5-shot)	24.99
TruthfulQA (0-shot)	50.62
Winogrande (5-shot)	48.62
GSM8K (5-shot)	0.0
DROP (3-shot)	1.32