metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: base_bert_ner_model
results: []
base_bert_ner_model
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7122
- Precision: 0.2260
- Recall: 0.0256
- F1: 0.0460
- Accuracy: 0.8504
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: 2e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 299 | 0.7522 | 0.1667 | 0.0008 | 0.0015 | 0.8492 |
| 0.7628 | 2.0 | 598 | 0.7353 | 0.2466 | 0.0140 | 0.0264 | 0.8499 |
| 0.7628 | 3.0 | 897 | 0.7247 | 0.2273 | 0.0233 | 0.0422 | 0.8509 |
| 0.7019 | 4.0 | 1196 | 0.7177 | 0.2619 | 0.0256 | 0.0466 | 0.8521 |
| 0.7019 | 5.0 | 1495 | 0.7122 | 0.2260 | 0.0256 | 0.0460 | 0.8504 |
Framework versions
- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2