metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner_0
results: []
bert-finetuned-ner_0
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2298
- Precision: 0.5119
- Recall: 0.4222
- F1: 0.4627
- Accuracy: 0.9246
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 250 | 0.2364 | 0.4874 | 0.2996 | 0.3711 | 0.9186 |
| 0.2444 | 2.0 | 500 | 0.2219 | 0.5112 | 0.3887 | 0.4416 | 0.9233 |
| 0.2444 | 3.0 | 750 | 0.2298 | 0.5119 | 0.4222 | 0.4627 | 0.9246 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1