SCoder-APPS – AI Model by AdnanRiaz107 | AlphaNeural AI

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AdnanRiaz107/
SCoder-APPS

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text-generation

generated_from_trainer

bigcode/santacoder

bigcode-openrail-m

autotrain_compatible

text-generation-inference

endpoints_compatible

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SCoder-APPS

This model is a fine-tuned version of bigcode/santacoder on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8114

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss
1.006	0.04	200	1.0234
0.9936	0.08	400	0.9176
0.9287	0.12	600	0.9170
0.8434	0.16	800	0.8872
0.8223	0.2	1000	0.8750
0.8129	0.24	1200	0.8720
0.8612	0.28	1400	0.8624
0.777	0.32	1600	0.8426
0.7444	0.36	1800	0.8453
0.6214	0.4	2000	0.8428
0.6856	0.44	2200	0.8365
0.6463	0.48	2400	0.8379
0.5872	0.52	2600	0.8226
0.6271	0.56	2800	0.8132
0.5772	0.6	3000	0.8237
0.568	0.64	3200	0.8097
0.5718	0.68	3400	0.8025
0.5407	0.72	3600	0.8222
0.4531	0.76	3800	0.8164
0.5571	0.8	4000	0.8209
0.4933	0.84	4200	0.8218
0.4749	0.88	4400	0.8176
0.4907	0.92	4600	0.8137
0.5014	0.96	4800	0.8118
0.4701	1.0	5000	0.8114

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2