---
license: apache-2.0
base_model: mpalaval/bert-ner-3
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-4
  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-4

This model is a fine-tuned version of [mpalaval/bert-ner-3](https://huggingface.co/mpalaval/bert-ner-3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6352
- Precision: 0.2024
- Recall: 0.4674
- F1: 0.2825
- Accuracy: 0.8901

## 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   | 258  | 0.4728          | 0.1508    | 0.4021 | 0.2193 | 0.8795   |
| 0.0801        | 2.0   | 516  | 0.4265          | 0.1744    | 0.4124 | 0.2451 | 0.8906   |
| 0.0801        | 3.0   | 774  | 0.5207          | 0.1564    | 0.4296 | 0.2294 | 0.8761   |
| 0.0513        | 4.0   | 1032 | 0.4908          | 0.1718    | 0.4021 | 0.2407 | 0.8882   |
| 0.0513        | 5.0   | 1290 | 0.5247          | 0.1967    | 0.4089 | 0.2656 | 0.8988   |
| 0.0263        | 6.0   | 1548 | 0.5547          | 0.1902    | 0.4261 | 0.2630 | 0.8955   |
| 0.0263        | 7.0   | 1806 | 0.6413          | 0.1849    | 0.4639 | 0.2644 | 0.8836   |
| 0.0133        | 8.0   | 2064 | 0.6059          | 0.2035    | 0.4742 | 0.2848 | 0.8900   |
| 0.0133        | 9.0   | 2322 | 0.6311          | 0.2041    | 0.4742 | 0.2854 | 0.8906   |
| 0.0088        | 10.0  | 2580 | 0.6352          | 0.2024    | 0.4674 | 0.2825 | 0.8901   |


### Framework versions

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