exp1_10partition_modelo_asl9000

vania2911/exp1_10partition_modelo_asl9000

exp1_10partition_modelo_asl9000 is a machine learning model from vania2911. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
License: apache-2.0
Model type: marian
Access: Public
Created: Apr 2, 2025
Updated: Apr 2, 2025
SHA: 137a06df

Base models

Helsinki-NLP/opus-mt-es-es

Model card

From the Hugging Face model README

exp1_10partition_modelo_asl9000

This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-es on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1357
Model Preparation Time: 0.0034
Bleu Msl: 0
Bleu 1 Msl: 0
Bleu 2 Msl: 0
Bleu 3 Msl: 0
Bleu 4 Msl: 0
Ter Msl: 100
Bleu Asl: 0
Bleu 1 Asl: 0.9745
Bleu 2 Asl: 0.9564
Bleu 3 Asl: 0.9341
Bleu 4 Asl: 0.9078
Ter Asl: 2.9734

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: 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	225	0.1334	0.0034	100	0.9571	0.9312	0.9024	0.8699	5.3785
No log	2.0	450	0.1099	0.0034	100	0.9647	0.9415	0.9151	0.8850	4.3327
0.2754	3.0	675	0.1008	0.0034	100	0.9708	0.9513	0.9274	0.9001	3.7600
0.2754	4.0	900	0.0887	0.0034	100	0.9711	0.9534	0.9309	0.9048	3.6106
0.0473	5.0	1125	0.0895	0.0034	100	0.9696	0.9507	0.9277	0.9012	3.7351
0.0473	6.0	1350	0.0946	0.0034	100	0.9727	0.9543	0.9305	0.9035	3.3367
0.0246	7.0	1575	0.0969	0.0034	100	0.9749	0.9576	0.9359	0.9105	3.1125
0.0246	8.0	1800	0.0882	0.0034	100	0.9760	0.9603	0.9397	0.9156	2.9880
0.0176	9.0	2025	0.0980	0.0034	100	0.9745	0.9585	0.9377	0.9128	3.2122
0.0176	10.0	2250	0.0994	0.0034	100	0.9739	0.9560	0.9343	0.9083	3.3367
0.0176	11.0	2475	0.0974	0.0034	100	0.9762	0.9602	0.9396	0.9155	3.1624
0.0101	12.0	2700	0.0998	0.0034	100	0.9739	0.9563	0.9342	0.9076	3.2122
0.0101	13.0	2925	0.0980	0.0034	100	0.9755	0.9593	0.9383	0.9135	3.0129
0.0081	14.0	3150	0.1035	0.0034	100	0.9717	0.9533	0.9310	0.9051	3.5857
0.0081	15.0	3375	0.0962	0.0034	100	0.9758	0.9589	0.9379	0.9129	3.0876
0.007	16.0	3600	0.0952	0.0034	100	0.9263	0.9054	0.8797	0.8474	9.1633
0.007	17.0	3825	0.1029	0.0034	100	0.9701	0.9511	0.9274	0.8993	3.9094
0.005	18.0	4050	0.0979	0.0034	100	0.9732	0.9557	0.9335	0.9071	3.4114
0.005	19.0	4275	0.1002	0.0034	100	0.9739	0.9566	0.9345	0.9083	3.3118
0.0048	20.0	4500	0.0957	0.0034	100	0.9756	0.9590	0.9381	0.9136	3.0876
0.0048	21.0	4725	0.1006	0.0034	100	0.9747	0.9578	0.9367	0.9118	3.2122
0.0048	22.0	4950	0.0981	0.0034	100	0.9760	0.9594	0.9383	0.9134	3.0129
0.0024	23.0	5175	0.0991	0.0034	100	0.9762	0.9604	0.9398	0.9152	3.0876
0.0024	24.0	5400	0.0942	0.0034	100	0.9762	0.9602	0.9398	0.9153	3.0129
0.0028	25.0	5625	0.0963	0.0034	100	0.9775	0.9619	0.9418	0.9179	2.8386
0.0028	26.0	5850	0.0962	0.0034	100	0.9775	0.9620	0.9417	0.9177	2.9133
0.0016	27.0	6075	0.0965	0.0034	100	0.9780	0.9623	0.9420	0.9183	2.8137
0.0016	28.0	6300	0.0960	0.0034	100	0.9780	0.9624	0.9423	0.9185	2.8137
0.0011	29.0	6525	0.0958	0.0034	100	0.9775	0.9620	0.9418	0.9178	2.8635
0.0011	30.0	6750	0.0959	0.0034	100	0.9778	0.9622	0.9421	0.9181	2.8386

Framework versions

Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Library: transformers
Type: marian
License: apache-2.0
Created: Apr 2, 2025
Updated: Apr 2, 2025