metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-ime
results: []
bert-finetuned-ner-ime
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4592
- Precision: 0.6456
- Recall: 0.3813
- F1: 0.4794
- Accuracy: 0.6108
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 | 221 | 2.6044 | 0.6263 | 0.3774 | 0.4710 | 0.6081 |
| No log | 2.0 | 442 | 2.5040 | 0.6286 | 0.3848 | 0.4774 | 0.6100 |
| 2.7612 | 3.0 | 663 | 2.4592 | 0.6456 | 0.3813 | 0.4794 | 0.6108 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.11.0