exp1_10partition_modelo9000

vania2911/exp1_10partition_modelo9000

exp1_10partition_modelo9000 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. --

Downloads · 30 days

6% of all-time downloads

All-time downloads

Public

Parameters

61.2M

8.1 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors245 MB · 99%

At a glance

Library: transformers
License: apache-2.0
Model type: marian
Access: Public
Created: Mar 16, 2025
Updated: Mar 26, 2025
SHA: e40347f3

Base models

Helsinki-NLP/opus-mt-es-es

Model card

From the Hugging Face model README

exp1_10partition_modelo9000

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: 0.7492
Model Preparation Time: 0.0049
Bleu Msl: 0
Bleu 1 Msl: 0.7877
Bleu 2 Msl: 0.6701
Bleu 3 Msl: 0.5934
Bleu 4 Msl: 0.5057
Ter Msl: 31.9909
Bleu Asl: 0
Bleu 1 Asl: 0.9668
Bleu 2 Asl: 0.9490
Bleu 3 Asl: 0.9272
Bleu 4 Asl: 0.8987
Ter Asl: 4.1176

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	Bleu 1 Msl	Bleu 2 Msl	Bleu 3 Msl	Bleu 4 Msl	Ter Msl	Bleu 1 Asl	Bleu 2 Asl	Bleu 3 Asl	Bleu 4 Asl	Ter Asl
No log	1.0	225	0.3414	0.0049	0.8217	0.7593	0.6876	0.5664	23.2578	0.9399	0.9041	0.8675	0.8270	7.4288
No log	2.0	450	0.2770	0.0049	0.8527	0.7879	0.7104	0.5930	21.7464	0.9581	0.9312	0.9040	0.8735	5.0126
0.4738	3.0	675	0.2653	0.0049	0.8642	0.8091	0.7464	0.6360	19.8153	0.9675	0.9457	0.9214	0.8928	4.0029
0.4738	4.0	900	0.2708	0.0049	0.8372	0.7858	0.7228	0.6126	21.2427	0.9604	0.9360	0.9109	0.8823	4.7241
0.0823	5.0	1125	0.2615	0.0049	0.8642	0.8075	0.7488	0.6515	20.3191	0.9645	0.9431	0.9203	0.8936	4.1832
0.0823	6.0	1350	0.2768	0.0049	0.7286	0.6666	0.5956	0.4899	41.3098	0.8344	0.8029	0.7687	0.7246	22.2863
0.0441	7.0	1575	0.2917	0.0049	0.8412	0.7835	0.7112	0.5945	20.9068	0.9678	0.9467	0.9242	0.8976	4.1111
0.0441	8.0	1800	0.2729	0.0049	0.8458	0.7909	0.7301	0.6287	18.7238	0.9704	0.9508	0.9295	0.9041	3.5701
0.0294	9.0	2025	0.2944	0.0049	0.8404	0.7712	0.6997	0.5950	21.9144	0.9685	0.9488	0.9277	0.9028	3.7505
0.0294	10.0	2250	0.2702	0.0049	0.8552	0.7927	0.7219	0.6148	19.6474	0.9655	0.9457	0.9247	0.9001	4.0750
0.0294	11.0	2475	0.2753	0.0049	0.8563	0.7929	0.7218	0.6159	21.2427	0.9688	0.9485	0.9260	0.8998	3.7865
0.0214	12.0	2700	0.2631	0.0049	0.8507	0.7936	0.7298	0.6288	19.1436	0.9704	0.9507	0.9290	0.9042	3.6423
0.0214	13.0	2925	0.2897	0.0049	0.8526	0.7939	0.7308	0.6291	19.3955	0.9655	0.9462	0.9246	0.8988	4.0029
0.0142	14.0	3150	0.2763	0.0049	0.8414	0.7851	0.7219	0.6247	20.5709	0.9686	0.9490	0.9273	0.9024	3.7144
0.0142	15.0	3375	0.2882	0.0049	0.8461	0.7808	0.7112	0.6074	20.2351	0.9745	0.9572	0.9378	0.9149	3.1735
0.0113	16.0	3600	0.2712	0.0049	0.8526	0.7883	0.7111	0.5978	19.5634	0.9738	0.9567	0.9368	0.9134	3.2456
0.0113	17.0	3825	0.2899	0.0049	0.8459	0.7788	0.7053	0.5981	19.8153	0.9723	0.9540	0.9343	0.9111	3.3898
0.0094	18.0	4050	0.2962	0.0049	0.8429	0.7788	0.7044	0.5902	21.0747	0.9701	0.9519	0.9315	0.9077	3.6423
0.0094	19.0	4275	0.2855	0.0049	0.8596	0.7984	0.7262	0.6185	19.2275	0.9754	0.9580	0.9392	0.9168	2.9931
0.0075	20.0	4500	0.2864	0.0049	0.8507	0.7936	0.7277	0.6206	19.8153	0.9699	0.9518	0.9324	0.9092	3.5701
0.0075	21.0	4725	0.2843	0.0049	0.8509	0.7880	0.7164	0.6099	20.6549	0.9742	0.9573	0.9388	0.9165	3.2095
0.0075	22.0	4950	0.3010	0.0049	0.8507	0.7911	0.7223	0.6177	21.3266	0.9738	0.9561	0.9369	0.9140	3.1735
0.0058	23.0	5175	0.2967	0.0049	0.8478	0.7907	0.7218	0.6155	20.7389	0.9723	0.9542	0.9349	0.9117	3.2816
0.0058	24.0	5400	0.2965	0.0049	0.8516	0.7908	0.7202	0.6111	21.2427	0.9754	0.9580	0.9392	0.9165	2.9931
0.0052	25.0	5625	0.2902	0.0049	0.8553	0.7922	0.7211	0.6146	21.1587	0.8396	0.8118	0.7820	0.7425	21.3487
0.0052	26.0	5850	0.2839	0.0049	0.8546	0.7997	0.7348	0.6313	19.5634	0.9723	0.9534	0.9337	0.9106	3.3177
0.0052	27.0	6075	0.2886	0.0049	0.8460	0.7860	0.7179	0.6125	20.6549	0.9745	0.9570	0.9380	0.9152	3.1013
0.0052	28.0	6300	0.2930	0.0049	0.8519	0.7882	0.7171	0.6100	20.9068	0.9732	0.9557	0.9363	0.9134	3.2816
0.0038	29.0	6525	0.2905	0.0049	0.8517	0.7905	0.7208	0.6141	20.8228	0.9732	0.9557	0.9363	0.9133	3.2456
0.0038	30.0	6750	0.2905	0.0049	0.8517	0.7905	0.7208	0.6141	20.8228	0.9735	0.9562	0.9372	0.9145	3.2095

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

Library: transformers
Type: marian
License: apache-2.0
Created: Mar 16, 2025
Updated: Mar 26, 2025