metadata
license: apache-2.0
base_model: google-bert/bert-large-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-uncased-finetuned-ner-geocorpus
results: []
bert-large-uncased-finetuned-ner-geocorpus
This model is a fine-tuned version of google-bert/bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1293
- Precision: 0.8171
- Recall: 0.8806
- F1: 0.8476
- Accuracy: 0.9721
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.9955 | 137 | 0.2292 | 0.4527 | 0.3450 | 0.3916 | 0.9378 |
| No log | 1.9982 | 275 | 0.1339 | 0.6814 | 0.7175 | 0.6990 | 0.9606 |
| No log | 2.9936 | 412 | 0.1147 | 0.7385 | 0.8057 | 0.7706 | 0.9647 |
| 0.2052 | 3.9964 | 550 | 0.1217 | 0.7099 | 0.8607 | 0.7781 | 0.9611 |
| 0.2052 | 4.9991 | 688 | 0.1076 | 0.7705 | 0.8531 | 0.8097 | 0.9674 |
| 0.2052 | 5.9946 | 825 | 0.1130 | 0.7970 | 0.8483 | 0.8219 | 0.9701 |
| 0.2052 | 6.9973 | 963 | 0.1332 | 0.7357 | 0.8758 | 0.7997 | 0.9637 |
| 0.0384 | 8.0 | 1101 | 0.1241 | 0.7798 | 0.8929 | 0.8325 | 0.9690 |
| 0.0384 | 8.9955 | 1238 | 0.1241 | 0.8303 | 0.8720 | 0.8507 | 0.9728 |
| 0.0384 | 9.9546 | 1370 | 0.1293 | 0.8171 | 0.8806 | 0.8476 | 0.9721 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1