esp-to-lsm-barto-model
This model is a fine-tuned version of vgaraujov/bart-base-spanish on Spanish-Mexican Sign Language (MSL) glosses dataset. It achieves the following results on the evaluation set:
- Loss: 0.0118
- Bleu: 82.2615
- Rouge: {'rouge1': 0.9459411340293693, 'rouge2': 0.8725612535612537, 'rougeL': 0.9409690603514131, 'rougeLsum': 0.9414154570919278}
- Ter: 7.9703
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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Ter |
|---|---|---|---|---|---|---|
| 0.0862 | 1.0 | 85 | 0.0441 | 48.0832 | {'rouge1': 0.7799851292498354, 'rouge2': 0.6094051319051321, 'rougeL': 0.7634691389764923, 'rougeLsum': 0.7637001348324879} | 34.4764 |
| 0.0323 | 2.0 | 170 | 0.0214 | 72.9928 | {'rouge1': 0.884157046828874, 'rouge2': 0.7702001337442517, 'rougeL': 0.8722237432043938, 'rougeLsum': 0.8720308750417114} | 16.6821 |
| 0.0198 | 3.0 | 255 | 0.0161 | 78.5669 | {'rouge1': 0.9199390239390244, 'rouge2': 0.82409139009139, 'rougeL': 0.911472143869203, 'rougeLsum': 0.9116302602626135} | 12.0482 |
| 0.0162 | 4.0 | 340 | 0.0143 | 79.2390 | {'rouge1': 0.9243402735608619, 'rouge2': 0.8460535205535207, 'rougeL': 0.9158039177598002, 'rougeLsum': 0.9159157335039689} | 10.7507 |
| 0.0137 | 5.0 | 425 | 0.0137 | 82.3938 | {'rouge1': 0.9334139504286565, 'rouge2': 0.8579696784696786, 'rougeL': 0.9274591149591148, 'rougeLsum': 0.927894385026738} | 9.6386 |
| 0.0108 | 6.0 | 510 | 0.0128 | 84.1329 | {'rouge1': 0.9350887445887449, 'rouge2': 0.8754486161986161, 'rougeL': 0.9311620617944146, 'rougeLsum': 0.9313348612172142} | 9.0825 |
| 0.0098 | 7.0 | 595 | 0.0129 | 79.7416 | {'rouge1': 0.9399191766838828, 'rouge2': 0.8716096403596405, 'rougeL': 0.9330582073155609, 'rougeLsum': 0.933733249865603} | 9.4532 |
| 0.009 | 8.0 | 680 | 0.0125 | 82.9321 | {'rouge1': 0.9443956476530007, 'rouge2': 0.8689144281644281, 'rougeL': 0.9390896358543419, 'rougeLsum': 0.9394144809438929} | 8.8971 |
| 0.0084 | 9.0 | 765 | 0.0122 | 81.9698 | {'rouge1': 0.946071417961124, 'rouge2': 0.8742369759869761, 'rougeL': 0.9409199134199135, 'rougeLsum': 0.9414803284950346} | 9.0825 |
| 0.0068 | 10.0 | 850 | 0.0121 | 81.9526 | {'rouge1': 0.9484588107970461, 'rouge2': 0.8778730158730159, 'rougeL': 0.9433170783464899, 'rougeLsum': 0.9437279305661661} | 8.4337 |
| 0.0078 | 11.0 | 935 | 0.0118 | 82.4911 | {'rouge1': 0.9460536750830865, 'rouge2': 0.8745218762718765, 'rougeL': 0.9401823225793814, 'rougeLsum': 0.9404524821583646} | 8.8044 |
| 0.0063 | 12.0 | 1020 | 0.0120 | 81.7252 | {'rouge1': 0.9465396825396828, 'rouge2': 0.8755185185185186, 'rougeL': 0.9404898777692895, 'rougeLsum': 0.941089275103981} | 8.8044 |
| 0.0069 | 13.0 | 1105 | 0.0121 | 81.7348 | {'rouge1': 0.9456640068308027, 'rouge2': 0.8716636381048146, 'rougeL': 0.940350419274568, 'rougeLsum': 0.941292909747631} | 8.5264 |
| 0.0059 | 14.0 | 1190 | 0.0120 | 82.7243 | {'rouge1': 0.9473343307019777, 'rouge2': 0.8731392958892958, 'rougeL': 0.9422385620915033, 'rougeLsum': 0.9425819221628045} | 8.4337 |
| 0.006 | 15.0 | 1275 | 0.0118 | 81.2037 | {'rouge1': 0.9470927234530175, 'rouge2': 0.8718730158730159, 'rougeL': 0.942004562431033, 'rougeLsum': 0.9425554706731177} | 8.3411 |
| 0.0055 | 16.0 | 1360 | 0.0119 | 82.1601 | {'rouge1': 0.9435703038791275, 'rouge2': 0.8706992266992267, 'rougeL': 0.938448826500297, 'rougeLsum': 0.9388509252185724} | 8.1557 |
| 0.0055 | 17.0 | 1445 | 0.0119 | 82.0465 | {'rouge1': 0.9453517120564336, 'rouge2': 0.8718517740429506, 'rougeL': 0.9403101408825094, 'rougeLsum': 0.940731923391366} | 8.0630 |
| 0.0051 | 18.0 | 1530 | 0.0118 | 82.1849 | {'rouge1': 0.9452478036669215, 'rouge2': 0.8716373626373629, 'rougeL': 0.9402017337237925, 'rougeLsum': 0.9406384008148714} | 8.0630 |
| 0.0055 | 19.0 | 1615 | 0.0118 | 82.0985 | {'rouge1': 0.9452005559799677, 'rouge2': 0.8723565323565323, 'rougeL': 0.9399868644427471, 'rougeLsum': 0.9405265469824293} | 8.0630 |
| 0.0052 | 20.0 | 1700 | 0.0118 | 82.2615 | {'rouge1': 0.9459411340293693, 'rouge2': 0.8725612535612537, 'rougeL': 0.9409690603514131, 'rougeLsum': 0.9414154570919278} | 7.9703 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
vgaraujov/bart-base-spanish