Instructions to use NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1") model = AutoModelForSequenceClassification.from_pretrained("NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1756
- F1 Micro: 0.7011
- F1 Macro: 0.3457
- Exact Match: 0.6951
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Exact Match |
|---|---|---|---|---|---|---|
| 0.1868 | 0.9924 | 131 | 0.1927 | 0.5934 | 0.1227 | 0.6610 |
| 0.1735 | 1.9848 | 262 | 0.1710 | 0.6306 | 0.1930 | 0.6761 |
| 0.1444 | 2.9773 | 393 | 0.1603 | 0.6493 | 0.2080 | 0.6818 |
| 0.1296 | 3.9697 | 524 | 0.1595 | 0.6701 | 0.3347 | 0.6894 |
| 0.0904 | 4.9621 | 655 | 0.1648 | 0.6778 | 0.3392 | 0.6913 |
| 0.0765 | 5.9545 | 786 | 0.1673 | 0.7050 | 0.3494 | 0.6989 |
| 0.0749 | 6.9470 | 917 | 0.1737 | 0.6833 | 0.3425 | 0.6894 |
| 0.0628 | 7.9394 | 1048 | 0.1756 | 0.7011 | 0.3457 | 0.6951 |
Framework versions
- Transformers 5.6.2
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for NiGuLa/dccuchile_bert-base-spanish-wwm-cased_ep10_lr1e-05_batchpergpu16_gpu1
Base model
dccuchile/bert-base-spanish-wwm-cased