---
license: mit
base_model: romainlhardy/roberta-large-finetuned-ner
tags:
- generated_from_trainer
model-index:
- name: roberta-large-finetuned-ner-finetuned-ner
  results: []
datasets:
- surrey-nlp/PLOD-filtered
---

<!-- 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-finetuned-ner-finetuned-ner

This model is a fine-tuned version of [romainlhardy/roberta-large-finetuned-ner](https://huggingface.co/romainlhardy/roberta-large-finetuned-ner) on surrey-nlp/PLOD-filtered dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.1264
- eval_precision: 0.9593
- eval_recall: 0.9473
- eval_f1: 0.9533
- eval_accuracy: 0.9488
- eval_runtime: 588.3236
- eval_samples_per_second: 41.032
- eval_steps_per_second: 10.258
- epoch: 0.59
- step: 16493

## label description

['B-O', 'B-AC', 'I-AC', 'B-LF', 'I-LF']

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2