metadata
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bluesky-spanish-classifier
results: []
bluesky-spanish-classifier
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3731
- Classification Report: {'ar': {'precision': 0.4898785425101215, 'recall': 0.32180851063829785, 'f1-score': 0.3884430176565008, 'support': 376.0}, 'cl': {'precision': 0.3626666666666667, 'recall': 0.4722222222222222, 'f1-score': 0.41025641025641024, 'support': 576.0}, 'co': {'precision': 0.34656084656084657, 'recall': 0.3808139534883721, 'f1-score': 0.3628808864265928, 'support': 344.0}, 'es': {'precision': 0.4630738522954092, 'recall': 0.427255985267035, 'f1-score': 0.4444444444444444, 'support': 543.0}, 'mx': {'precision': 0.43380855397148677, 'recall': 0.43917525773195876, 'f1-score': 0.4364754098360656, 'support': 485.0}, 'pe': {'precision': 0.3769968051118211, 'recall': 0.3390804597701149, 'f1-score': 0.35703479576399394, 'support': 348.0}, 'pr': {'precision': 0.5736434108527132, 'recall': 0.7326732673267327, 'f1-score': 0.6434782608695652, 'support': 101.0}, 'uy': {'precision': 0.35096153846153844, 'recall': 0.3201754385964912, 'f1-score': 0.3348623853211009, 'support': 228.0}, 've': {'precision': 0.16666666666666666, 'recall': 0.045454545454545456, 'f1-score': 0.07142857142857142, 'support': 22.0}, 'accuracy': 0.4085345683096262, 'macro avg': {'precision': 0.39602854256636333, 'recall': 0.38651773783286336, 'f1-score': 0.3832560202225828, 'support': 3023.0}, 'weighted avg': {'precision': 0.4124949665181113, 'recall': 0.4085345683096262, 'f1-score': 0.40601279016852304, 'support': 3023.0}}
- F1: 0.3833
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: 2.8600231011639855e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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
- lr_scheduler_warmup_ratio: 0.11531859504380029
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Classification Report | F1 |
|---|---|---|---|---|---|
| 1.7603 | 1.0 | 882 | 1.7406 | {'ar': {'precision': 0.35516372795969775, 'recall': 0.375, 'f1-score': 0.3648124191461837, 'support': 376.0}, 'cl': {'precision': 0.3016759776536313, 'recall': 0.28125, 'f1-score': 0.29110512129380056, 'support': 576.0}, 'co': {'precision': 0.3670886075949367, 'recall': 0.25290697674418605, 'f1-score': 0.29948364888123924, 'support': 344.0}, 'es': {'precision': 0.3584905660377358, 'recall': 0.4548802946593002, 'f1-score': 0.400974025974026, 'support': 543.0}, 'mx': {'precision': 0.32465753424657534, 'recall': 0.488659793814433, 'f1-score': 0.39012345679012345, 'support': 485.0}, 'pe': {'precision': 0.3958333333333333, 'recall': 0.27298850574712646, 'f1-score': 0.3231292517006803, 'support': 348.0}, 'pr': {'precision': 0.5631067961165048, 'recall': 0.5742574257425742, 'f1-score': 0.5686274509803921, 'support': 101.0}, 'uy': {'precision': 0.4666666666666667, 'recall': 0.18421052631578946, 'f1-score': 0.2641509433962264, 'support': 228.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.3536222295732716, 'macro avg': {'precision': 0.34807591217878686, 'recall': 0.3204615025581566, 'f1-score': 0.32248959090696355, 'support': 3023.0}, 'weighted avg': {'precision': 0.35948675942105285, 'recall': 0.3536222295732716, 'f1-score': 0.3456546260541325, 'support': 3023.0}} | 0.3225 |
| 1.4223 | 2.0 | 1764 | 1.6758 | {'ar': {'precision': 0.4349315068493151, 'recall': 0.3377659574468085, 'f1-score': 0.38023952095808383, 'support': 376.0}, 'cl': {'precision': 0.336996336996337, 'recall': 0.3194444444444444, 'f1-score': 0.32798573975044565, 'support': 576.0}, 'co': {'precision': 0.36333333333333334, 'recall': 0.3168604651162791, 'f1-score': 0.3385093167701863, 'support': 344.0}, 'es': {'precision': 0.38980716253443526, 'recall': 0.5211786372007366, 'f1-score': 0.44602048857368004, 'support': 543.0}, 'mx': {'precision': 0.35246995994659547, 'recall': 0.5443298969072164, 'f1-score': 0.42787682333873583, 'support': 485.0}, 'pe': {'precision': 0.44308943089430897, 'recall': 0.3132183908045977, 'f1-score': 0.367003367003367, 'support': 348.0}, 'pr': {'precision': 0.759493670886076, 'recall': 0.594059405940594, 'f1-score': 0.6666666666666666, 'support': 101.0}, 'uy': {'precision': 0.5542168674698795, 'recall': 0.20175438596491227, 'f1-score': 0.2958199356913183, 'support': 228.0}, 've': {'precision': 1.0, 'recall': 0.09090909090909091, 'f1-score': 0.16666666666666666, 'support': 22.0}, 'accuracy': 0.3916639100231558, 'macro avg': {'precision': 0.5149264743233645, 'recall': 0.35994674163718665, 'f1-score': 0.3796431694910167, 'support': 3023.0}, 'weighted avg': {'precision': 0.4116802685001794, 'recall': 0.3916639100231558, 'f1-score': 0.3851176158170783, 'support': 3023.0}} | 0.3796 |
| 0.9068 | 3.0 | 2646 | 1.9523 | {'ar': {'precision': 0.39574468085106385, 'recall': 0.4946808510638298, 'f1-score': 0.4397163120567376, 'support': 376.0}, 'cl': {'precision': 0.35144927536231885, 'recall': 0.3368055555555556, 'f1-score': 0.34397163120567376, 'support': 576.0}, 'co': {'precision': 0.31555555555555553, 'recall': 0.4127906976744186, 'f1-score': 0.35768261964735515, 'support': 344.0}, 'es': {'precision': 0.47113163972286376, 'recall': 0.3756906077348066, 'f1-score': 0.4180327868852459, 'support': 543.0}, 'mx': {'precision': 0.43680709534368073, 'recall': 0.4061855670103093, 'f1-score': 0.42094017094017094, 'support': 485.0}, 'pe': {'precision': 0.38661710037174724, 'recall': 0.2988505747126437, 'f1-score': 0.3371150729335494, 'support': 348.0}, 'pr': {'precision': 0.64, 'recall': 0.6336633663366337, 'f1-score': 0.6368159203980099, 'support': 101.0}, 'uy': {'precision': 0.30662020905923343, 'recall': 0.38596491228070173, 'f1-score': 0.341747572815534, 'support': 228.0}, 've': {'precision': 0.18181818181818182, 'recall': 0.09090909090909091, 'f1-score': 0.12121212121212122, 'support': 22.0}, 'accuracy': 0.3906715183592458, 'macro avg': {'precision': 0.3873048597871828, 'recall': 0.3817268025864433, 'f1-score': 0.37969268978826637, 'support': 3023.0}, 'weighted avg': {'precision': 0.3971399185993649, 'recall': 0.3906715183592458, 'f1-score': 0.3902981034934984, 'support': 3023.0}} | 0.3797 |
| 0.4818 | 4.0 | 3528 | 2.3731 | {'ar': {'precision': 0.4898785425101215, 'recall': 0.32180851063829785, 'f1-score': 0.3884430176565008, 'support': 376.0}, 'cl': {'precision': 0.3626666666666667, 'recall': 0.4722222222222222, 'f1-score': 0.41025641025641024, 'support': 576.0}, 'co': {'precision': 0.34656084656084657, 'recall': 0.3808139534883721, 'f1-score': 0.3628808864265928, 'support': 344.0}, 'es': {'precision': 0.4630738522954092, 'recall': 0.427255985267035, 'f1-score': 0.4444444444444444, 'support': 543.0}, 'mx': {'precision': 0.43380855397148677, 'recall': 0.43917525773195876, 'f1-score': 0.4364754098360656, 'support': 485.0}, 'pe': {'precision': 0.3769968051118211, 'recall': 0.3390804597701149, 'f1-score': 0.35703479576399394, 'support': 348.0}, 'pr': {'precision': 0.5736434108527132, 'recall': 0.7326732673267327, 'f1-score': 0.6434782608695652, 'support': 101.0}, 'uy': {'precision': 0.35096153846153844, 'recall': 0.3201754385964912, 'f1-score': 0.3348623853211009, 'support': 228.0}, 've': {'precision': 0.16666666666666666, 'recall': 0.045454545454545456, 'f1-score': 0.07142857142857142, 'support': 22.0}, 'accuracy': 0.4085345683096262, 'macro avg': {'precision': 0.39602854256636333, 'recall': 0.38651773783286336, 'f1-score': 0.3832560202225828, 'support': 3023.0}, 'weighted avg': {'precision': 0.4124949665181113, 'recall': 0.4085345683096262, 'f1-score': 0.40601279016852304, 'support': 3023.0}} | 0.3833 |
| 0.2357 | 5.0 | 4410 | 2.7721 | {'ar': {'precision': 0.42168674698795183, 'recall': 0.3723404255319149, 'f1-score': 0.3954802259887006, 'support': 376.0}, 'cl': {'precision': 0.38753799392097266, 'recall': 0.4427083333333333, 'f1-score': 0.413290113452188, 'support': 576.0}, 'co': {'precision': 0.35051546391752575, 'recall': 0.3953488372093023, 'f1-score': 0.37158469945355194, 'support': 344.0}, 'es': {'precision': 0.4642857142857143, 'recall': 0.40699815837937386, 'f1-score': 0.4337585868498528, 'support': 543.0}, 'mx': {'precision': 0.43089430894308944, 'recall': 0.43711340206185567, 'f1-score': 0.43398157625383826, 'support': 485.0}, 'pe': {'precision': 0.3407960199004975, 'recall': 0.3936781609195402, 'f1-score': 0.36533333333333334, 'support': 348.0}, 'pr': {'precision': 0.6601941747572816, 'recall': 0.6732673267326733, 'f1-score': 0.6666666666666666, 'support': 101.0}, 'uy': {'precision': 0.40853658536585363, 'recall': 0.29385964912280704, 'f1-score': 0.34183673469387754, 'support': 228.0}, 've': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 22.0}, 'accuracy': 0.40886536553092956, 'macro avg': {'precision': 0.3849385564532096, 'recall': 0.3794793659212001, 'f1-score': 0.38021465963244544, 'support': 3023.0}, 'weighted avg': {'precision': 0.41080624270175103, 'recall': 0.40886536553092956, 'f1-score': 0.4078732692419294, 'support': 3023.0}} | 0.3802 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0