WizardCoder1B-StaproCoder – AI Model by rreit | AlphaNeural AI | AlphaNeural AI

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WizardCoder1B-StaproCoder

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WizardLM/WizardCoder-1B-V1.0

bigcode-openrail-m

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WizardCoder1B-StaproCoder

This model is a fine-tuned version of WizardLM/WizardCoder-1B-V1.0 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2618

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: 12
eval_batch_size: 12
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 48
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss
0.3982	0.05	100	0.3337
0.3102	0.1	200	0.2979
0.3561	0.15	300	0.2811
0.299	0.2	400	0.2739
0.2599	0.25	500	0.2702
0.2105	0.3	600	0.2671
0.2772	0.35	700	0.2638
0.2038	0.4	800	0.2626
0.2102	0.45	900	0.2627
0.2527	0.5	1000	0.2606
0.2137	0.55	1100	0.2606
0.1793	0.6	1200	0.2622
0.1655	0.65	1300	0.2618
0.228	0.7	1400	0.2616
0.1542	0.75	1500	0.2611
0.194	0.8	1600	0.2614
0.2056	0.85	1700	0.2612
0.2081	0.9	1800	0.2615
0.1824	0.95	1900	0.2618
0.1841	1.0	2000	0.2618

Framework versions

PEFT 0.9.0
Transformers 4.39.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.17.1
Tokenizers 0.15.2