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---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBert_NER_finer
results: []
datasets:
- nlpaueb/finer-139
language:
- en
pipeline_tag: token-classification
---
<!-- 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. -->
# distilBert_NER_finer
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the [Finer-139](https://huggingface.co/datasets/nlpaueb/finer-139) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0198
- Precision: 0.9445
- Recall: 0.9640
- F1: 0.9541
- Accuracy: 0.9954
## Training and evaluation data
The training data consists of the 4 most widely available ner_tags from the Finer-139 dataset. The training and the test data were curated from this source accordingly
## 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
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0034 | 1.0 | 1620 | 0.0261 | 0.9167 | 0.9668 | 0.9411 | 0.9941 |
| 0.0031 | 2.0 | 3240 | 0.0182 | 0.9471 | 0.9651 | 0.9561 | 0.9956 |
| 0.0012 | 3.0 | 4860 | 0.0198 | 0.9445 | 0.9640 | 0.9541 | 0.9954 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |