---
library_name: transformers
base_model: YituTech/conv-bert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: convbert-finetuned-ner
  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. -->

# convbert-finetuned-ner

This model is a fine-tuned version of [YituTech/conv-bert-base](https://huggingface.co/YituTech/conv-bert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1088
- Precision: 0.9589
- Recall: 0.9707
- F1: 0.9648
- Accuracy: 0.9805

## 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: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.074         | 1.0   | 5285  | 0.1325          | 0.9499    | 0.9621 | 0.9560 | 0.9744   |
| 0.0658        | 2.0   | 10570 | 0.1142          | 0.9567    | 0.9679 | 0.9623 | 0.9788   |
| 0.0908        | 3.0   | 15855 | 0.1088          | 0.9589    | 0.9707 | 0.9648 | 0.9805   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1