This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.7005
Accuracy: 0.455

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.183	0.16	20	1.4843	0.35
1.34	0.32	40	1.4466	0.35
1.265	0.48	60	1.3036	0.39
1.3107	0.64	80	1.2656	0.415
1.0969	0.8	100	1.2302	0.455
1.1958	0.96	120	1.2676	0.465
1.0183	1.12	140	1.2523	0.45
0.8682	1.28	160	1.2620	0.495
0.9	1.44	180	1.2779	0.485
0.9613	1.6	200	1.5713	0.36
0.9667	1.76	220	1.3170	0.465
1.0284	1.92	240	1.2343	0.5
0.8681	2.08	260	1.2968	0.49
0.7134	2.24	280	1.4032	0.44
0.7311	2.4	300	1.3624	0.46
0.61	2.56	320	1.4416	0.44
0.7033	2.7200	340	1.5110	0.46
0.5881	2.88	360	1.3926	0.475
0.6666	3.04	380	1.3896	0.49
0.4299	3.2	400	1.4787	0.47
0.3613	3.36	420	1.5145	0.48
0.4714	3.52	440	1.5547	0.46
0.4698	3.68	460	1.5584	0.44
0.3191	3.84	480	1.5748	0.475
0.4044	4.0	500	1.7353	0.44
0.2275	4.16	520	1.6115	0.46
0.3171	4.32	540	1.6326	0.46
0.2005	4.48	560	1.6569	0.47
0.3165	4.64	580	1.6955	0.46
0.2543	4.8	600	1.6887	0.465
0.186	4.96	620	1.7005	0.455

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1

miguelpezo/segundaprueba

segundaprueba

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

miguelpezo/
segundaprueba