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	75	0.2877	0.0032	100	0.9471	0.9143	0.8823	0.8467	6.5089
No log	2.0	150	0.1600	0.0032	100	0.9560	0.9262	0.8951	0.8600	5.6213
No log	3.0	225	0.1465	0.0032	100	0.9625	0.9350	0.9076	0.8760	4.7337
No log	4.0	300	0.1421	0.0032	100	0.9670	0.9445	0.9201	0.8903	4.0680
No log	5.0	375	0.1441	0.0032	100	0.9607	0.9355	0.9092	0.8786	4.8077
No log	6.0	450	0.1509	0.0032	100	0.9612	0.9368	0.9113	0.8811	4.8817
0.2184	7.0	525	0.1463	0.0032	100	0.9651	0.9412	0.9155	0.8841	4.2160
0.2184	8.0	600	0.1574	0.0032	100	0.9430	0.9164	0.8878	0.8535	7.0266
0.2184	9.0	675	0.1478	0.0032	100	0.9628	0.9401	0.9157	0.8855	4.4379
0.2184	10.0	750	0.1471	0.0032	100	0.9659	0.9437	0.9198	0.8901	4.0680
0.2184	11.0	825	0.1511	0.0032	100	0.9658	0.9428	0.9183	0.8881	4.2899
0.2184	12.0	900	0.1446	0.0032	100	0.9665	0.9428	0.9177	0.8867	3.9201
0.2184	13.0	975	0.1470	0.0032	100	0.9683	0.9456	0.9218	0.8934	3.8462
0.013	14.0	1050	0.1504	0.0032	100	0.9671	0.9431	0.9179	0.8876	3.8462
0.013	15.0	1125	0.1497	0.0032	100	0.9678	0.9438	0.9180	0.8873	3.7722
0.013	16.0	1200	0.1616	0.0032	100	0.9652	0.9409	0.9152	0.8845	4.1420
0.013	17.0	1275	0.1578	0.0032	100	0.9671	0.9447	0.9204	0.8913	3.8462
0.013	18.0	1350	0.1534	0.0032	100	0.9659	0.9425	0.9183	0.8890	3.9941
0.013	19.0	1425	0.1526	0.0032	100	0.9677	0.9453	0.9217	0.8939	3.6982
0.0058	20.0	1500	0.1574	0.0032	100	0.9684	0.9466	0.9230	0.8939	3.6243
0.0058	21.0	1575	0.1563	0.0032	100	0.9684	0.9469	0.9242	0.8961	3.7722
0.0058	22.0	1650	0.1575	0.0032	100	0.9690	0.9476	0.9249	0.8970	3.6243
0.0058	23.0	1725	0.1589	0.0032	100	0.9678	0.9459	0.9223	0.8931	3.6243
0.0058	24.0	1800	0.1628	0.0032	100	0.9671	0.9451	0.9214	0.8920	3.7722
0.0058	25.0	1875	0.1576	0.0032	100	0.9678	0.9454	0.9216	0.8922	3.6982
0.0058	26.0	1950	0.1564	0.0032	100	0.9697	0.9480	0.9246	0.8958	3.4024
0.0029	27.0	2025	0.1555	0.0032	100	0.9697	0.9480	0.9246	0.8957	3.4763
0.0029	28.0	2100	0.1561	0.0032	100	0.9691	0.9469	0.9229	0.8935	3.5503
0.0029	29.0	2175	0.1559	0.0032	100	0.9697	0.9480	0.9246	0.8955	3.4763
0.0029	30.0	2250	0.1561	0.0032	100	0.9691	0.9469	0.9229	0.8935	3.5503

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

vania2911/exp2_10partition_modelo_asl3000

exp2_10partition_modelo_asl3000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vania2911/
exp2_10partition_modelo_asl3000