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Erland/
result_xlmr_siqa

Name: result_xlmr_siqa
Availability: InStock

generated_from_trainer

super_glue

FacebookAI/xlm-roberta-large

finetune

mit

endpoints_compatible

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result_xlmr_siqa

This model is a fine-tuned version of xlm-roberta-large on the super_glue dataset. It trained first on SIQA dataset. It achieves the following results on the evaluation set:

Loss: 1.4143
Accuracy: 0.79

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
train_batch_size: 8
eval_batch_size: 8
seed: 44
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0152	0.2	10	1.0207	0.77
0.001	0.4	20	0.7651	0.82
0.0013	0.6	30	0.7756	0.79
0.0012	0.8	40	1.2054	0.8
0.0005	1.0	50	1.3034	0.79
0.0008	1.2	60	1.1920	0.76
0.0138	1.4	70	0.9139	0.76
0.0003	1.6	80	0.9160	0.78
0.0001	1.8	90	1.1525	0.8
0.0085	2.0	100	0.8657	0.79
0.0033	2.2	110	0.8925	0.79
0.0055	2.4	120	1.2264	0.78
0.0014	2.6	130	1.4958	0.8
0.0031	2.8	140	1.4250	0.79
0.0138	3.0	150	1.4240	0.81
0.0304	3.2	160	1.4179	0.8
0.0	3.4	170	1.4685	0.8
0.0	3.6	180	1.4897	0.8
0.0015	3.8	190	1.2689	0.8
0.0001	4.0	200	1.0355	0.78
0.0007	4.2	210	1.1339	0.77
0.0002	4.4	220	1.1915	0.79
0.0001	4.6	230	1.1300	0.8
0.001	4.8	240	1.1464	0.79
0.0001	5.0	250	1.2227	0.78
0.0	5.2	260	1.3048	0.81
0.0	5.4	270	1.3418	0.79
0.0093	5.6	280	1.3442	0.78
0.0004	5.8	290	1.2721	0.8
0.0035	6.0	300	1.1852	0.77
0.0016	6.2	310	1.1745	0.77
0.0003	6.4	320	1.1138	0.8
0.0002	6.6	330	1.2342	0.79
0.0055	6.8	340	1.3594	0.79
0.0	7.0	350	1.4109	0.79
0.0	7.2	360	1.4677	0.78
0.0	7.4	370	1.4951	0.77
0.0	7.6	380	1.4987	0.77
0.0004	7.8	390	1.4517	0.77
0.0	8.0	400	1.4632	0.77
0.0	8.2	410	1.4825	0.78
0.0008	8.4	420	1.4486	0.79
0.0	8.6	430	1.4426	0.79
0.0	8.8	440	1.4216	0.79
0.0	9.0	450	1.4166	0.79
0.0	9.2	460	1.4161	0.79
0.0	9.4	470	1.4172	0.79
0.0003	9.6	480	1.4179	0.79
0.0286	9.8	490	1.4155	0.79
0.0	10.0	500	1.4143	0.79

Framework versions

Transformers 4.34.0
Pytorch 2.1.0
Datasets 2.14.5
Tokenizers 0.14.0

Erland/result_xlmr_siqa

result_xlmr_siqa

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Erland/
result_xlmr_siqa