---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-crf-ner-conll2003
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-crf-ner-conll2003

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: 0.7776
- Precision: 0.9454
- Recall: 0.9495
- F1: 0.9474
- Accuracy: 0.9908

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7572        | 1.0   | 878  | 0.7882          | 0.9112    | 0.9253 | 0.9182 | 0.9868   |
| 0.2013        | 2.0   | 1756 | 0.7316          | 0.9384    | 0.9456 | 0.9420 | 0.9898   |
| 0.1517        | 3.0   | 2634 | 0.7776          | 0.9454    | 0.9495 | 0.9474 | 0.9908   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2