---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-finetuned-ner4
  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-base-cased-finetuned-ner4

This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2239
- Precision: 0.8342
- Recall: 0.8511
- F1: 0.8426
- Accuracy: 0.9648

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1257        | 1.0   | 38000  | 0.1357          | 0.8006    | 0.8311 | 0.8155 | 0.9604   |
| 0.0954        | 2.0   | 76000  | 0.1530          | 0.8278    | 0.8347 | 0.8312 | 0.9627   |
| 0.0897        | 3.0   | 114000 | 0.1539          | 0.8302    | 0.8449 | 0.8375 | 0.9647   |
| 0.0411        | 4.0   | 152000 | 0.1971          | 0.8321    | 0.8504 | 0.8411 | 0.9648   |
| 0.0205        | 5.0   | 190000 | 0.2239          | 0.8342    | 0.8511 | 0.8426 | 0.9648   |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.5.1+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1