metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_BIOMAT_NER_1000
results: []
BERT_BIOMAT_NER_1000
This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3920
- Precision: 0.9495
- Recall: 0.9444
- F1: 0.9470
- Accuracy: 0.9380
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: 32
- eval_batch_size: 32
- seed: 42
- 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 | 1.0 | 211 | 0.2669 | 0.9407 | 0.9352 | 0.9380 | 0.9275 |
| No log | 2.0 | 422 | 0.2809 | 0.9457 | 0.9432 | 0.9444 | 0.9343 |
| 0.2064 | 3.0 | 633 | 0.3114 | 0.9472 | 0.9454 | 0.9463 | 0.9353 |
| 0.2064 | 4.0 | 844 | 0.3323 | 0.9491 | 0.9422 | 0.9456 | 0.9358 |
| 0.0481 | 5.0 | 1055 | 0.3478 | 0.9493 | 0.9441 | 0.9467 | 0.9382 |
| 0.0481 | 6.0 | 1266 | 0.3731 | 0.9486 | 0.9438 | 0.9462 | 0.9374 |
| 0.0481 | 7.0 | 1477 | 0.3723 | 0.9491 | 0.9445 | 0.9468 | 0.9379 |
| 0.0201 | 8.0 | 1688 | 0.3830 | 0.9489 | 0.9443 | 0.9466 | 0.9369 |
| 0.0201 | 9.0 | 1899 | 0.3873 | 0.9503 | 0.9448 | 0.9475 | 0.9378 |
| 0.0106 | 10.0 | 2110 | 0.3920 | 0.9495 | 0.9444 | 0.9470 | 0.9380 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1