---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: RoBERTa-Base-full-finetuned-ner-multi-label
  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-Base-full-finetuned-ner-multi-label

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0484
- F1 Micro: 0.8025
- Precision Micro: 0.8296
- Recall Micro: 0.7772

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|
| No log        | 1.0   | 27   | 0.1227          | 0.6758   | 0.7555          | 0.6114       |
| No log        | 2.0   | 54   | 0.0750          | 0.7087   | 0.9323          | 0.5716       |
| No log        | 3.0   | 81   | 0.0628          | 0.7597   | 0.8531          | 0.6848       |
| No log        | 4.0   | 108  | 0.0554          | 0.7868   | 0.8768          | 0.7136       |
| No log        | 5.0   | 135  | 0.0522          | 0.7987   | 0.8228          | 0.7759       |
| No log        | 6.0   | 162  | 0.0508          | 0.7967   | 0.8283          | 0.7674       |
| No log        | 7.0   | 189  | 0.0493          | 0.8005   | 0.8263          | 0.7763       |
| No log        | 8.0   | 216  | 0.0489          | 0.8032   | 0.8253          | 0.7822       |
| No log        | 9.0   | 243  | 0.0490          | 0.8014   | 0.8171          | 0.7864       |
| No log        | 10.0  | 270  | 0.0484          | 0.8025   | 0.8296          | 0.7772       |


### Framework versions

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