---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-ner-3

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5646
- Precision: 0.1708
- Recall: 0.4296
- F1: 0.2444
- Accuracy: 0.8849

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 211  | 0.3086          | 0.1551    | 0.2612 | 0.1946 | 0.9151   |
| No log        | 2.0   | 422  | 0.3039          | 0.1730    | 0.3608 | 0.2339 | 0.9091   |
| 0.3957        | 3.0   | 633  | 0.3823          | 0.1396    | 0.3608 | 0.2013 | 0.8904   |
| 0.3957        | 4.0   | 844  | 0.4147          | 0.1592    | 0.3780 | 0.2240 | 0.8862   |
| 0.1085        | 5.0   | 1055 | 0.4257          | 0.1785    | 0.3814 | 0.2432 | 0.8963   |
| 0.1085        | 6.0   | 1266 | 0.5030          | 0.1575    | 0.4055 | 0.2269 | 0.8797   |
| 0.1085        | 7.0   | 1477 | 0.5427          | 0.1509    | 0.3883 | 0.2173 | 0.8784   |
| 0.0488        | 8.0   | 1688 | 0.5601          | 0.1673    | 0.4467 | 0.2434 | 0.8775   |
| 0.0488        | 9.0   | 1899 | 0.5518          | 0.1707    | 0.4124 | 0.2414 | 0.8880   |
| 0.0243        | 10.0  | 2110 | 0.5646          | 0.1708    | 0.4296 | 0.2444 | 0.8849   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1