learning_rate: 0.0001
train_batch_size: 32
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Ter Msl	Bleu 1 Asl	Bleu 2 Asl	Bleu 3 Asl	Bleu 4 Asl	Ter Asl
No log	1.0	150	0.1715	0.0034	100	0.9510	0.9205	0.8886	0.8535	5.9367
No log	2.0	300	0.1202	0.0034	100	0.9683	0.9475	0.9243	0.8963	4.0882
No log	3.0	450	0.1128	0.0034	100	0.9689	0.9476	0.9237	0.8956	3.9104
0.2629	4.0	600	0.1179	0.0034	100	0.9714	0.9519	0.9288	0.9022	3.4838
0.2629	5.0	750	0.1103	0.0034	100	0.9715	0.9523	0.9297	0.9022	3.5194
0.2629	6.0	900	0.1103	0.0034	100	0.9724	0.9525	0.9288	0.9005	3.4483
0.0327	7.0	1050	0.1116	0.0034	100	0.9705	0.9499	0.9273	0.9002	3.7327
0.0327	8.0	1200	0.1067	0.0034	100	0.9736	0.9542	0.9311	0.9039	3.2705
0.0327	9.0	1350	0.1060	0.0034	100	0.9739	0.9554	0.9334	0.9068	3.2705
0.0142	10.0	1500	0.1117	0.0034	100	0.9743	0.9559	0.9354	0.9103	3.1639
0.0142	11.0	1650	0.1044	0.0034	100	0.9740	0.9556	0.9341	0.9091	3.0217
0.0142	12.0	1800	0.1055	0.0034	100	0.9768	0.9595	0.9383	0.9124	2.8084
0.0142	13.0	1950	0.1005	0.0034	100	0.9793	0.9636	0.9446	0.9213	2.5240
0.0094	14.0	2100	0.1058	0.0034	100	0.9752	0.9574	0.9356	0.9098	2.9150
0.0094	15.0	2250	0.1161	0.0034	100	0.9765	0.9589	0.9372	0.9110	2.8795
0.0094	16.0	2400	0.1240	0.0034	100	0.9730	0.9538	0.9308	0.9037	3.3416
0.0067	17.0	2550	0.1137	0.0034	100	0.9746	0.9563	0.9339	0.9074	3.0572
0.0067	18.0	2700	0.1157	0.0034	100	0.9752	0.9570	0.9348	0.9085	2.9150
0.0067	19.0	2850	0.1068	0.0034	100	0.9768	0.9589	0.9373	0.9117	2.7728
0.0042	20.0	3000	0.1111	0.0034	100	0.9771	0.9598	0.9387	0.9133	2.7017
0.0042	21.0	3150	0.1073	0.0034	100	0.9746	0.9565	0.9350	0.9093	2.9506
0.0042	22.0	3300	0.1097	0.0034	100	0.9756	0.9582	0.9372	0.9118	2.8439
0.0042	23.0	3450	0.1132	0.0034	100	0.9780	0.9612	0.9407	0.9161	2.6662
0.0029	24.0	3600	0.1119	0.0034	100	0.9777	0.9607	0.9399	0.9148	2.7373
0.0029	25.0	3750	0.1105	0.0034	100	0.9771	0.9607	0.9404	0.9161	2.7373
0.0029	26.0	3900	0.1104	0.0034	100	0.9774	0.9608	0.9403	0.9154	2.7373
0.0017	27.0	4050	0.1103	0.0034	100	0.9777	0.9613	0.9409	0.9162	2.6662
0.0017	28.0	4200	0.1102	0.0034	100	0.9774	0.9606	0.9396	0.9144	2.7017
0.0017	29.0	4350	0.1109	0.0034	100	0.9771	0.9602	0.9392	0.9139	2.7373
0.0013	30.0	4500	0.1107	0.0034	100	0.9768	0.9597	0.9384	0.9126	2.7728

Framework versions

Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

vania2911/exp3_10partition_modelo_asl6000

exp3_10partition_modelo_asl6000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vania2911/
exp3_10partition_modelo_asl6000