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sharoz/codeparrot-small-custom-functions-dataset-python

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

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codeparrot-small-custom-functions-dataset-python

This model is a fine-tuned version of codeparrot/codeparrot-small on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.4238

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: 2e-05
—trainbatchsize: 8
—evalbatchsize: 8
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
1.216	0.12	1	1.0747
1.051	0.25	2	1.0005
0.9855	0.38	3	0.9462
0.9259	0.5	4	0.9042
0.9236	0.62	5	0.8675
0.8644	0.75	6	0.8331
0.8148	0.88	7	0.8030
0.7554	1.0	8	0.7800
0.7815	1.12	9	0.7600
0.784	1.25	10	0.7440
0.635	1.38	11	0.7309
0.6666	1.5	12	0.7170
0.7676	1.62	13	0.6993
0.6608	1.75	14	0.6835
0.6885	1.88	15	0.6696
0.69	2.0	16	0.6582
0.6343	2.12	17	0.6463
0.709	2.25	18	0.6324
0.5446	2.38	19	0.6206
0.5298	2.5	20	0.6102
0.6478	2.62	21	0.6016
0.546	2.75	22	0.5941
0.6297	2.88	23	0.5871
0.4518	3.0	24	0.5814
0.566	3.12	25	0.5769
0.6285	3.25	26	0.5702
0.5938	3.38	27	0.5631
0.514	3.5	28	0.5568
0.5113	3.62	29	0.5504
0.512	3.75	30	0.5451
0.4392	3.88	31	0.5407
0.5097	4.0	32	0.5370
0.4866	4.12	33	0.5326
0.5028	4.25	34	0.5285
0.5438	4.38	35	0.5228
0.5424	4.5	36	0.5166
0.5156	4.62	37	0.5108
0.4335	4.75	38	0.5056
0.4298	4.88	39	0.5013
0.5268	5.0	40	0.4978
0.4714	5.12	41	0.4938
0.4659	5.25	42	0.4907
0.4573	5.38	43	0.4874
0.4689	5.5	44	0.4847
0.4346	5.62	45	0.4824
0.4563	5.75	46	0.4794
0.4505	5.88	47	0.4761
0.7359	6.0	48	0.4732
0.4704	6.12	49	0.4706
0.4223	6.25	50	0.4685
0.4789	6.38	51	0.4651
0.4402	6.5	52	0.4624
0.4454	6.62	53	0.4597
0.4496	6.75	54	0.4566
0.3942	6.88	55	0.4539
0.2915	7.0	56	0.4515
0.3926	7.12	57	0.4496
0.4102	7.25	58	0.4474
0.4235	7.38	59	0.4456
0.4841	7.5	60	0.4441
0.3914	7.62	61	0.4423
0.4417	7.75	62	0.4404
0.4212	7.88	63	0.4384
0.4343	8.0	64	0.4369
0.4159	8.12	65	0.4355
0.4193	8.25	66	0.4343
0.4393	8.38	67	0.4333
0.4507	8.5	68	0.4319
0.3855	8.62	69	0.4305
0.4064	8.75	70	0.4293
0.4044	8.88	71	0.4283
0.2957	9.0	72	0.4275
0.4442	9.12	73	0.4266
0.4142	9.25	74	0.4260
0.4022	9.38	75	0.4253
0.4161	9.5	76	0.4248
0.3828	9.62	77	0.4244
0.384	9.75	78	0.4241
0.3985	9.88	79	0.4239
0.4912	10.0	80	0.4238

Framework versions

—Transformers 4.28.1
—Pytorch 2.0.0+cu118
—Datasets 2.12.0
—Tokenizers 0.13.3