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gokuls/sa_bert_12_layer_modified_complete_training_48

sourceHugging Faceupdated 3y agoView on Hugging Face

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sabert12layermodifiedcompletetraining_48

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. It achieves the following results on the evaluation set:

—Loss: 2.7897
—Accuracy: 0.5117

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: 1e-05
—trainbatchsize: 32
—evalbatchsize: 32
—seed: 10
—distributed_type: multi-GPU
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—lrschedulerwarmup_steps: 10000
—num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.5942	0.05	10000	6.5714	0.1229
6.1563	0.11	20000	6.3437	0.1392
6.1425	0.16	30000	6.2474	0.1444
6.2249	0.22	40000	6.1900	0.1468
6.1498	0.27	50000	6.1482	0.1487
6.0528	0.33	60000	6.1192	0.1492
6.0103	0.38	70000	6.0762	0.1504
5.8523	0.44	80000	5.8731	0.1615
5.91	0.49	90000	5.7442	0.1765
5.4931	0.55	100000	5.5985	0.1952
5.4145	0.6	110000	5.4716	0.2100
5.3729	0.66	120000	5.3366	0.2247
5.2655	0.71	130000	5.1946	0.2417
5.2975	0.76	140000	5.0287	0.2600
4.9997	0.82	150000	4.8593	0.2791
4.831	0.87	160000	4.6226	0.3041
4.9176	0.93	170000	4.4211	0.3257
4.5352	0.98	180000	4.2328	0.3429
4.1536	1.04	190000	4.0635	0.3598
4.0216	1.09	200000	3.9109	0.3755
4.0744	1.15	210000	3.7761	0.3897
3.7468	1.2	220000	3.6636	0.4038
3.5015	1.26	230000	3.5047	0.4236
3.5717	1.31	240000	3.4014	0.4370
3.1969	1.37	250000	3.3173	0.4479
3.5026	1.42	260000	3.2254	0.4588
3.287	1.47	270000	3.1845	0.4643
3.3462	1.53	280000	3.0979	0.4738
3.3996	1.58	290000	3.0808	0.4764
3.2324	1.64	300000	3.0163	0.4843
3.0972	1.69	310000	2.9738	0.4890
3.1621	1.75	320000	2.9450	0.4927
3.0282	1.8	330000	2.9135	0.4964
3.0674	1.86	340000	2.9059	0.4979
2.9437	1.91	350000	2.8810	0.5007
2.8208	1.97	360000	2.8316	0.5064
2.9005	2.02	370000	2.8061	0.5098
2.7574	2.08	380000	2.7897	0.5117

Framework versions

—Transformers 4.30.2
—Pytorch 1.14.0a0+410ce96
—Datasets 2.13.0
—Tokenizers 0.13.3