metadata
license: apache-2.0
base_model: google-bert/bert-large-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-cased-finetuned-ner-harem
results: []
bert-large-cased-finetuned-ner-harem
This model is a fine-tuned version of google-bert/bert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2665
- Precision: 0.7241
- Recall: 0.7423
- F1: 0.7331
- Accuracy: 0.9611
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 | 0.9938 | 140 | 0.2609 | 0.5107 | 0.5626 | 0.5354 | 0.9324 |
| No log | 1.9947 | 281 | 0.2057 | 0.6370 | 0.6642 | 0.6503 | 0.9517 |
| No log | 2.9956 | 422 | 0.2106 | 0.6527 | 0.6642 | 0.6584 | 0.9566 |
| 0.2074 | 3.9965 | 563 | 0.2342 | 0.6843 | 0.7054 | 0.6947 | 0.9571 |
| 0.2074 | 4.9973 | 704 | 0.2369 | 0.7216 | 0.7290 | 0.7253 | 0.9614 |
| 0.2074 | 5.9982 | 845 | 0.2334 | 0.7013 | 0.7261 | 0.7135 | 0.9574 |
| 0.2074 | 6.9991 | 986 | 0.2580 | 0.7139 | 0.7570 | 0.7348 | 0.9592 |
| 0.0377 | 8.0 | 1127 | 0.2658 | 0.7452 | 0.7452 | 0.7452 | 0.9607 |
| 0.0377 | 8.9938 | 1267 | 0.2619 | 0.7543 | 0.7688 | 0.7615 | 0.9637 |
| 0.0377 | 9.9379 | 1400 | 0.2665 | 0.7241 | 0.7423 | 0.7331 | 0.9611 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1