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	0.3132	0.0057	100	0.9322	0.8912	0.8487	0.8031	8.3276
No log	2.0	150	0.2020	0.0057	100	0.9411	0.9047	0.8689	0.8275	7.3720
No log	3.0	225	0.1637	0.0057	100	0.9544	0.9266	0.8978	0.8648	5.5973
No log	4.0	300	0.1428	0.0057	100	0.8362	0.8040	0.7701	0.7270	4.9829
No log	5.0	375	0.1314	0.0057	100	0.8392	0.8086	0.7765	0.7348	4.2321
No log	6.0	450	0.1407	0.0057	100	0.9645	0.9412	0.9174	0.8885	4.3686
0.2194	7.0	525	0.1272	0.0057	100	0.9646	0.9412	0.9170	0.8874	4.3003
0.2194	8.0	600	0.1392	0.0057	100	0.9622	0.9386	0.9141	0.8847	4.5051
0.2194	9.0	675	0.1359	0.0057	100	0.9652	0.9429	0.9197	0.8920	4.2321
0.2194	10.0	750	0.1361	0.0057	100	0.9657	0.9432	0.9198	0.8920	4.2321
0.2194	11.0	825	0.1383	0.0057	100	0.9681	0.9475	0.9257	0.8997	3.6860
0.2194	12.0	900	0.1364	0.0057	100	0.9675	0.9467	0.9243	0.8976	3.9590
0.2194	13.0	975	0.1301	0.0057	100	0.9693	0.9492	0.9280	0.9031	3.4812
0.0119	14.0	1050	0.1261	0.0057	100	0.9699	0.9503	0.9295	0.9043	3.4130
0.0119	15.0	1125	0.1326	0.0057	100	0.9676	0.9471	0.9256	0.8987	3.8908
0.0119	16.0	1200	0.1274	0.0057	100	0.9687	0.9481	0.9263	0.9007	3.6177
0.0119	17.0	1275	0.1319	0.0057	100	0.9699	0.9499	0.9285	0.9031	3.4812
0.0119	18.0	1350	0.1312	0.0057	100	0.9717	0.9523	0.9316	0.9067	3.2082
0.0119	19.0	1425	0.1336	0.0057	100	0.9687	0.9477	0.9256	0.8994	3.6177
0.0044	20.0	1500	0.1345	0.0057	100	0.9687	0.9490	0.9281	0.9028	3.4812
0.0044	21.0	1575	0.1321	0.0057	100	0.9705	0.9502	0.9280	0.9014	3.3447
0.0044	22.0	1650	0.1346	0.0057	100	0.9693	0.9485	0.9256	0.8987	3.4812
0.0044	23.0	1725	0.1366	0.0057	100	0.9687	0.9482	0.9262	0.9003	3.4812
0.0044	24.0	1800	0.1390	0.0057	100	0.9663	0.9445	0.9204	0.8925	3.8225
0.0044	25.0	1875	0.1375	0.0057	100	0.9669	0.9455	0.9222	0.8950	3.7543
0.0044	26.0	1950	0.1362	0.0057	100	0.9675	0.9461	0.9230	0.8955	3.6860
0.0025	27.0	2025	0.1351	0.0057	100	0.9681	0.9471	0.9245	0.8972	3.6177
0.0025	28.0	2100	0.1342	0.0057	100	0.9675	0.9461	0.9230	0.8955	3.6860
0.0025	29.0	2175	0.1348	0.0057	100	0.9669	0.9451	0.9213	0.8933	3.7543
0.0025	30.0	2250	0.1350	0.0057	100	0.9669	0.9451	0.9213	0.8933	3.7543

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

vania2911/exp1_10partition_modelo_asl3000

exp1_10partition_modelo_asl3000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vania2911/
exp1_10partition_modelo_asl3000