---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa-Large-full-finetuned-ner-single
  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-Large-full-finetuned-ner-single

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2870
- Precision: 0.8934
- Recall: 0.8934
- F1: 0.8934
- Accuracy: 0.8934

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 27   | 0.3242          | 0.8691    | 0.8689 | 0.8690 | 0.8689   |
| No log        | 2.0   | 54   | 0.3003          | 0.8684    | 0.8692 | 0.8688 | 0.8692   |
| No log        | 3.0   | 81   | 0.2860          | 0.8839    | 0.8859 | 0.8845 | 0.8859   |
| No log        | 4.0   | 108  | 0.2870          | 0.8934    | 0.8934 | 0.8934 | 0.8934   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1