---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta_crf_ner_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. -->

# roberta_crf_ner_finetuned

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.7893
- Recall: 0.6294
- F1: 0.6950
- Accuracy: 0.8037

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0           | 1.0   | 85   | nan             | 1.0       | 0.0    | 0.0    | 0.7707   |
| 0.0           | 2.0   | 170  | nan             | 0.5437    | 0.1932 | 0.1694 | 0.8848   |
| 0.0           | 3.0   | 255  | nan             | 0.4412    | 0.3360 | 0.3230 | 0.9228   |
| 0.0           | 4.0   | 340  | nan             | 0.4888    | 0.6412 | 0.5523 | 0.9161   |
| 0.0           | 5.0   | 425  | nan             | 0.6312    | 0.6266 | 0.6206 | 0.9451   |
| 0.0           | 6.0   | 510  | nan             | 0.6319    | 0.6851 | 0.6560 | 0.9484   |
| 0.0           | 7.0   | 595  | nan             | 0.6655    | 0.7110 | 0.6869 | 0.9518   |
| 0.0           | 8.0   | 680  | nan             | 0.6341    | 0.7094 | 0.6693 | 0.9508   |
| 0.0           | 9.0   | 765  | nan             | 0.6745    | 0.7127 | 0.6924 | 0.9533   |
| 0.0           | 10.0  | 850  | nan             | 0.6886    | 0.7175 | 0.7019 | 0.9548   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1