---
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: 0.8044
- Recall: 0.6309
- F1: 0.7014
- Accuracy: 0.8064

## 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             | 0.5105    | 0.1412 | 0.1284 | 0.8910   |
| 0.0           | 3.0   | 255  | nan             | 0.3443    | 0.3458 | 0.3346 | 0.9210   |
| 0.0           | 4.0   | 340  | nan             | 0.5898    | 0.5990 | 0.5930 | 0.9423   |
| 0.0           | 5.0   | 425  | nan             | 0.5650    | 0.5795 | 0.5606 | 0.9421   |
| 0.0           | 6.0   | 510  | nan             | 0.6261    | 0.6867 | 0.6515 | 0.9470   |
| 0.0           | 7.0   | 595  | nan             | 0.6874    | 0.6640 | 0.6724 | 0.9457   |
| 0.0           | 8.0   | 680  | nan             | 0.6825    | 0.7224 | 0.7011 | 0.9549   |
| 0.0           | 9.0   | 765  | nan             | 0.6744    | 0.7224 | 0.6972 | 0.9551   |
| 0.0           | 10.0  | 850  | nan             | 0.7020    | 0.7062 | 0.7035 | 0.9552   |


### Framework versions

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