barto_exp1_10partition_modelo_msl9000

vania2911/barto_exp1_10partition_modelo_msl9000

barto_exp1_10partition_modelo_msl9000 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: bart
Access: Public
Created: Apr 15, 2025
Updated: Apr 16, 2025
SHA: 0c0423d5

Base models

vgaraujov/bart-base-spanish

Model card

From the Hugging Face model README

barto_exp1_10partition_modelo_msl9000

This model is a fine-tuned version of vgaraujov/bart-base-spanish on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4960
Model Preparation Time: 0.0056
Bleu Msl: 0
Bleu 1 Msl: 0.8086
Bleu 2 Msl: 0.7441
Bleu 3 Msl: 0.6848
Bleu 4 Msl: 0.5835
Ter Msl: 24.1228
Bleu Asl: 0
Bleu 1 Asl: 0.9818
Bleu 2 Asl: 0.9669
Bleu 3 Asl: 0.9485
Bleu 4 Asl: 0.9264
Ter Asl: 2.0278

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	0.3301	0.0056	0.8146	0.7241	0.6553	0.5580	22.9407	0.9593	0.9326	0.9053	0.8755	5.0133
No log	2.0	450	0.2479	0.0056	0.8706	0.8179	0.7650	0.6741	15.0576	0.9609	0.9353	0.9085	0.8778	4.8614
0.4382	3.0	675	0.2646	0.0056	0.8355	0.7407	0.6656	0.5501	18.8663	0.9732	0.9560	0.9365	0.9126	3.1903
0.4382	4.0	900	0.2865	0.0056	0.8395	0.7867	0.7364	0.6492	16.0319	0.9729	0.9547	0.9344	0.9102	3.4182
0.0856	5.0	1125	0.3001	0.0056	0.6942	0.6154	0.5419	0.4526	25.6864	0.9761	0.9604	0.9419	0.9201	2.8864
0.0856	6.0	1350	0.2791	0.0056	0.8284	0.7660	0.7068	0.6120	19.0434	0.9738	0.9565	0.9370	0.9132	3.3422
0.0492	7.0	1575	0.3060	0.0056	0.8044	0.7356	0.6741	0.5849	19.8406	0.9735	0.9547	0.9339	0.9082	3.2662
0.0492	8.0	1800	0.3230	0.0056	0.7931	0.6757	0.5879	0.4854	25.5979	0.9745	0.9574	0.9387	0.9161	3.1523
0.0344	9.0	2025	0.2935	0.0056	0.8312	0.7728	0.7138	0.6320	18.9548	0.9716	0.9539	0.9343	0.9105	3.4182
0.0344	10.0	2250	0.2862	0.0056	0.7703	0.6791	0.6071	0.5190	23.3835	0.9722	0.9556	0.9369	0.9141	3.2662
0.0344	11.0	2475	0.2891	0.0056	0.8084	0.7362	0.6689	0.5775	20.5492	0.9764	0.9603	0.9414	0.9183	2.7345
0.0233	12.0	2700	0.3214	0.0056	0.7989	0.7230	0.6543	0.5484	23.7378	0.9787	0.9637	0.9467	0.9257	2.5066
0.0233	13.0	2925	0.3377	0.0056	0.8345	0.7662	0.7035	0.6164	19.6634	0.9764	0.9613	0.9441	0.9226	2.8105
0.0171	14.0	3150	0.3142	0.0056	0.8276	0.7770	0.7231	0.6420	16.9176	0.9783	0.9635	0.9463	0.9251	2.5826
0.0171	15.0	3375	0.3416	0.0056	0.7555	0.6759	0.6036	0.5096	22.6749	0.9793	0.9651	0.9487	0.9280	2.5446
0.012	16.0	3600	0.3114	0.0056	0.8309	0.7624	0.6982	0.6022	18.3348	0.9745	0.9592	0.9417	0.9202	2.8864
0.012	17.0	3825	0.3250	0.0056	0.8369	0.7608	0.6953	0.6006	18.9548	0.9761	0.9595	0.9412	0.9183	3.1523
0.0097	18.0	4050	0.3011	0.0056	0.8052	0.7281	0.6589	0.5632	20.9920	0.9761	0.9593	0.9405	0.9174	3.0763
0.0097	19.0	4275	0.3326	0.0056	0.8163	0.7387	0.6672	0.5704	19.7520	0.9764	0.9605	0.9425	0.9202	2.8485
0.0065	20.0	4500	0.3216	0.0056	0.7911	0.7136	0.6439	0.5477	22.4092	0.9787	0.9630	0.9452	0.9230	2.6586
0.0065	21.0	4725	0.3671	0.0056	0.7975	0.7124	0.6407	0.5420	21.9663	0.9761	0.9603	0.9424	0.9200	2.8864
0.0065	22.0	4950	0.3547	0.0056	0.8034	0.7246	0.6558	0.5551	21.4349	0.9761	0.9596	0.9414	0.9189	2.9624
0.0051	23.0	5175	0.3530	0.0056	0.8076	0.7277	0.6583	0.5611	20.9035	0.9758	0.9592	0.9407	0.9179	3.0004
0.0051	24.0	5400	0.3531	0.0056	0.8041	0.7369	0.6732	0.5764	20.7263	0.9761	0.9598	0.9415	0.9189	2.8105
0.0035	25.0	5625	0.3439	0.0056	0.7976	0.7296	0.6670	0.5738	21.1692	0.9758	0.9596	0.9418	0.9196	2.8485
0.0035	26.0	5850	0.3522	0.0056	0.8124	0.7455	0.6837	0.5891	19.3091	0.9764	0.9605	0.9425	0.9204	2.8105
0.0034	27.0	6075	0.3768	0.0056	0.8062	0.7375	0.6735	0.5790	20.1063	0.9764	0.9605	0.9424	0.9201	2.8105
0.0034	28.0	6300	0.3592	0.0056	0.8070	0.7379	0.6738	0.5792	20.0177	0.9764	0.9602	0.9417	0.9189	2.8864
0.0026	29.0	6525	0.3571	0.0056	0.8114	0.7430	0.6802	0.5855	19.4863	0.9767	0.9606	0.9421	0.9194	2.8485
0.0026	30.0	6750	0.3563	0.0056	0.8106	0.7421	0.6790	0.5847	19.5748	0.9764	0.9602	0.9417	0.9189	2.8864

Framework versions

Transformers 4.51.1
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Library: transformers
Type: bart
License: apache-2.0
Created: Apr 15, 2025
Updated: Apr 16, 2025