---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa-large-PM-M3-Voc-hf-finetuned-ner-v2
  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-PM-M3-Voc-hf-finetuned-ner-v2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5003
- Precision: 0.3319
- Recall: 0.2149
- F1: 0.2609
- Accuracy: 0.8211

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 54   | 0.5106          | 0.2273    | 0.1003 | 0.1392 | 0.8194   |
| No log        | 2.0   | 108  | 0.4781          | 0.3122    | 0.2120 | 0.2526 | 0.8226   |
| No log        | 3.0   | 162  | 0.5003          | 0.3319    | 0.2149 | 0.2609 | 0.8211   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3