---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: dev-ner-ontonote-bert-finetuned
  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. -->

# dev-ner-ontonote-bert-finetuned

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0241
- Precision: 0.9404
- Recall: 0.9668
- F1: 0.9535
- Accuracy: 0.9937

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 267  | 0.1113          | 0.7576    | 0.7973 | 0.7769 | 0.9689   |
| 0.2811        | 2.0   | 534  | 0.0559          | 0.8732    | 0.9087 | 0.8906 | 0.9847   |
| 0.2811        | 3.0   | 801  | 0.0360          | 0.9147    | 0.9478 | 0.9309 | 0.9904   |
| 0.063         | 4.0   | 1068 | 0.0275          | 0.9333    | 0.9600 | 0.9465 | 0.9928   |
| 0.063         | 5.0   | 1335 | 0.0241          | 0.9404    | 0.9668 | 0.9535 | 0.9937   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.13.3