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	0.1387	0.0034	100	0.9596	0.9308	0.8999	0.8642	5.1005
No log	2.0	300	0.1095	0.0034	100	0.9698	0.9459	0.9200	0.8888	3.6113
No log	3.0	450	0.1068	0.0034	100	0.9677	0.9438	0.9175	0.8867	3.8347
0.2642	4.0	600	0.1017	0.0034	100	0.9743	0.9538	0.9319	0.9050	2.9412
0.2642	5.0	750	0.1086	0.0034	100	0.9680	0.9459	0.9221	0.8928	2.9784
0.2642	6.0	900	0.1100	0.0034	100	0.9007	0.8736	0.8435	0.8049	3.0529
0.0312	7.0	1050	0.1057	0.0034	100	0.9720	0.9530	0.9303	0.9033	3.2390
0.0312	8.0	1200	0.1105	0.0034	100	0.9782	0.9604	0.9405	0.9150	2.6806
0.0312	9.0	1350	0.1035	0.0034	100	0.9782	0.9602	0.9400	0.9147	2.5689
0.0156	10.0	1500	0.1028	0.0034	100	0.9749	0.9549	0.9325	0.9055	3.0529
0.0156	11.0	1650	0.1015	0.0034	100	0.9769	0.9580	0.9368	0.9110	2.6806
0.0156	12.0	1800	0.1001	0.0034	100	0.9798	0.9621	0.9419	0.9166	2.4944
0.0156	13.0	1950	0.1126	0.0034	100	0.9769	0.9576	0.9361	0.9094	2.8295
0.01	14.0	2100	0.1059	0.0034	100	0.9725	0.9532	0.9318	0.9046	3.2390
0.01	15.0	2250	0.1028	0.0034	100	0.9786	0.9609	0.9406	0.9149	2.5316
0.01	16.0	2400	0.1026	0.0034	100	0.9799	0.9635	0.9448	0.9205	2.3827
0.0072	17.0	2550	0.1032	0.0034	100	0.9763	0.9586	0.9383	0.9119	2.7550
0.0072	18.0	2700	0.1053	0.0034	100	0.9799	0.9631	0.9439	0.9193	2.2338
0.0072	19.0	2850	0.1063	0.0034	100	0.9802	0.9637	0.9444	0.9199	2.3083
0.0031	20.0	3000	0.1084	0.0034	100	0.9789	0.9632	0.9445	0.9205	2.4200
0.0031	21.0	3150	0.1098	0.0034	100	0.9799	0.9631	0.9439	0.9196	2.3455
0.0031	22.0	3300	0.1061	0.0034	100	0.9805	0.9643	0.9455	0.9215	2.2338
0.0031	23.0	3450	0.1085	0.0034	100	0.9795	0.9626	0.9431	0.9189	2.3455
0.0031	24.0	3600	0.1086	0.0034	100	0.9792	0.9622	0.9426	0.9178	2.4572
0.0031	25.0	3750	0.1086	0.0034	100	0.9792	0.9629	0.9438	0.9193	2.4200
0.0031	26.0	3900	0.1069	0.0034	100	0.9773	0.9606	0.9411	0.9164	2.5689
0.0017	27.0	4050	0.1080	0.0034	100	0.9805	0.9645	0.9458	0.9218	2.1966
0.0017	28.0	4200	0.1077	0.0034	100	0.9802	0.9639	0.9449	0.9206	2.2338
0.0017	29.0	4350	0.1069	0.0034	100	0.9805	0.9645	0.9456	0.9215	2.1593
0.0013	30.0	4500	0.1069	0.0034	100	0.9805	0.9645	0.9458	0.9218	2.1593

Framework versions

Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

vania2911/exp4_10partition_modelo_asl6000

exp4_10partition_modelo_asl6000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vania2911/
exp4_10partition_modelo_asl6000