roberta-base-bne-finetuned-recores2

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 8.9761
• Accuracy: 0.3113

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: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6094	1.0	1047	1.6094	0.2259
1.6094	2.0	2094	1.6094	0.2121
1.6094	3.0	3141	1.6094	0.2314
1.6094	4.0	4188	1.6094	0.1956
1.6094	5.0	5235	1.6094	0.2121
1.6121	6.0	6282	1.6094	0.1818
1.6094	7.0	7329	1.6094	0.2259
1.6092	8.0	8376	1.6094	0.1736
1.6094	9.0	9423	1.6094	0.1956
1.6094	10.0	10470	1.6094	0.1736
1.6094	11.0	11517	1.6094	0.1983
1.6094	12.0	12564	1.6094	0.2176
1.6094	13.0	13611	1.6094	0.1928
1.6096	14.0	14658	1.6094	0.1846
1.6145	15.0	15705	1.6094	0.2066
1.6094	16.0	16752	1.6022	0.2121
1.8471	17.0	17799	1.6101	0.1763
2.8148	18.0	18846	2.7585	0.2452
2.5445	19.0	19893	2.4576	0.2920
1.9972	20.0	20940	3.6002	0.2865
1.9844	21.0	21987	5.3809	0.3168
2.849	22.0	23034	7.2230	0.3140
1.4208	23.0	24081	8.0602	0.2975
0.4045	24.0	25128	8.2947	0.3058
0.3052	25.0	26175	8.9761	0.3113

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1