11661

vania2911/11661

11661 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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Hugging Face

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At a glance

Library: transformers
License: apache-2.0
Model type: marian
Access: Public
Created: Mar 9, 2025
Updated: Mar 10, 2025
SHA: 216a1dd9

Base models

Helsinki-NLP/opus-mt-es-es

Model card

From the Hugging Face model README

11661

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: 0.4527
Model Preparation Time: 0.0032
Bleu Msl: 0.0
Bleu 1 Msl: 0.6915
Bleu 2 Msl: 0.0153
Bleu 3 Msl: 0.0046
Bleu 4 Msl: 0.0023
Ter Msl: 100
Bleu Asl: 0
Bleu 1 Asl: 0
Bleu 2 Asl: 0
Bleu 3 Asl: 0
Bleu 4 Asl: 0
Ter Asl: 100

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 Msl	Bleu 1 Msl	Bleu 2 Msl	Bleu 3 Msl	Bleu 4 Msl	Ter Msl	Bleu Asl	Bleu 1 Asl	Bleu 2 Asl	Bleu 3 Asl	Bleu 4 Asl	Ter Asl
No log	1.0	292	0.1642	0.0032	100.0000	0.5547	0.0102	0.0028	0.0014	100	100.0000	0.5429	0.0055	0.0013	0.0006	100
0.1267	2.0	584	0.1476	0.0032	100.0000	0.5937	0.0105	0.0029	0.0014	100	100.0000	0.5351	0.0055	0.0013	0.0006	100
0.1267	3.0	876	0.1483	0.0032	100.0000	0.6122	0.0107	0.0029	0.0014	100	100.0000	0.5390	0.0055	0.0013	0.0006	100
0.063	4.0	1168	0.1353	0.0032	100.0000	0.5362	0.0100	0.0028	0.0014	100	100.0000	0.5624	0.0056	0.0013	0.0006	100
0.063	5.0	1460	0.1427	0.0032	100.0000	0.5993	0.0106	0.0029	0.0014	100	100.0000	0.5507	0.0055	0.0013	0.0006	100
0.0391	6.0	1752	0.1448	0.0032	100.0000	0.4137	0.0088	0.0026	0.0013	100	100.0000	0.5318	0.0054	0.0013	0.0006	100
0.0266	7.0	2044	0.1471	0.0032	100.0000	0.4898	0.0095	0.0027	0.0013	100	100.0000	0.5446	0.0055	0.0013	0.0006	100
0.0266	8.0	2336	0.1447	0.0032	100.0000	0.5659	0.0103	0.0029	0.0014	100	100.0000	0.5457	0.0055	0.0013	0.0006	100
0.0234	9.0	2628	0.1435	0.0032	100.0000	0.6289	0.0108	0.0030	0.0014	100	100.0000	0.5702	0.0056	0.0013	0.0006	100
0.0234	10.0	2920	0.1389	0.0032	100.0000	0.6308	0.0108	0.0030	0.0014	100	100.0000	0.5624	0.0056	0.0013	0.0006	100
0.0162	11.0	3212	0.1413	0.0032	100.0000	0.5881	0.0105	0.0029	0.0014	100	100.0000	0.5708	0.0056	0.0013	0.0006	100
0.0138	12.0	3504	0.1458	0.0032	100.0000	0.6215	0.0107	0.0029	0.0014	100	100.0000	0.5797	0.0057	0.0013	0.0006	100
0.0138	13.0	3796	0.1439	0.0032	100.0000	0.5250	0.0099	0.0028	0.0014	100	100.0000	0.5585	0.0056	0.0013	0.0006	100
0.0105	14.0	4088	0.1482	0.0032	100.0000	0.5325	0.0099	0.0028	0.0014	100	100.0000	0.5569	0.0056	0.0013	0.0006	100
0.0105	15.0	4380	0.1524	0.0032	100.0000	0.4657	0.0093	0.0027	0.0013	100	100.0000	0.5468	0.0055	0.0013	0.0006	100
0.0098	16.0	4672	0.1519	0.0032	100.0000	0.5121	0.0098	0.0028	0.0013	100	100.0000	0.5535	0.0056	0.0013	0.0006	100
0.0098	17.0	4964	0.1569	0.0032	100.0000	0.4416	0.0091	0.0026	0.0013	100	100.0000	0.5557	0.0056	0.0013	0.0006	100
0.0081	18.0	5256	0.1524	0.0032	100.0000	0.5028	0.0097	0.0028	0.0013	100	100.0000	0.5474	0.0055	0.0013	0.0006	100
0.0062	19.0	5548	0.1493	0.0032	100.0000	0.4935	0.0096	0.0027	0.0013	100	100.0000	0.5552	0.0056	0.0013	0.0006	100
0.0062	20.0	5840	0.1513	0.0032	100.0000	0.5566	0.0102	0.0028	0.0014	100	100.0000	0.5452	0.0055	0.0013	0.0006	100
0.0053	21.0	6132	0.1471	0.0032	100.0000	0.5380	0.0100	0.0028	0.0014	100	100.0000	0.5619	0.0056	0.0013	0.0006	100
0.0053	22.0	6424	0.1480	0.0032	100.0000	0.5288	0.0099	0.0028	0.0014	100	100.0000	0.5541	0.0056	0.0013	0.0006	100
0.0042	23.0	6716	0.1489	0.0032	100.0000	0.5473	0.0101	0.0028	0.0014	100	100.0000	0.5641	0.0056	0.0013	0.0006	100
0.0039	24.0	7008	0.1500	0.0032	100.0000	0.6327	0.0108	0.0030	0.0014	100	100.0000	0.5602	0.0056	0.0013	0.0006	100
0.0039	25.0	7300	0.1496	0.0032	100.0000	0.5900	0.0105	0.0029	0.0014	100	100.0000	0.5624	0.0056	0.0013	0.0006	100
0.0032	26.0	7592	0.1478	0.0032	100.0000	0.5659	0.0103	0.0029	0.0014	100	100.0000	0.5630	0.0056	0.0013	0.0006	100
0.0032	27.0	7884	0.1493	0.0032	100.0000	0.5455	0.0101	0.0028	0.0014	100	100.0000	0.5647	0.0056	0.0013	0.0006	100
0.0031	28.0	8176	0.1500	0.0032	100.0000	0.5455	0.0101	0.0028	0.0014	100	100.0000	0.5674	0.0056	0.0013	0.0006	100
0.0031	29.0	8468	0.1504	0.0032	100.0000	0.5417	0.0100	0.0028	0.0014	100	100.0000	0.5630	0.0056	0.0013	0.0006	100
0.0021	30.0	8760	0.1502	0.0032	100.0000	0.5399	0.0100	0.0028	0.0014	100	100.0000	0.5635	0.0056	0.0013	0.0006	100

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0

Library: transformers
Type: marian
License: apache-2.0
Created: Mar 9, 2025
Updated: Mar 10, 2025