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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- article250v5_wikigold_split
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Article_250v5_NER_Model_3Epochs_UNAUGMENTED
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: article250v5_wikigold_split
type: article250v5_wikigold_split
args: default
metrics:
- name: Precision
type: precision
value: 0.3979099678456592
- name: Recall
type: recall
value: 0.4221148379761228
- name: F1
type: f1
value: 0.4096551724137931
- name: Accuracy
type: accuracy
value: 0.8778839730743538
---
<!-- 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. -->
# Article_250v5_NER_Model_3Epochs_UNAUGMENTED
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the article250v5_wikigold_split dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3250
- Precision: 0.3979
- Recall: 0.4221
- F1: 0.4097
- Accuracy: 0.8779
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 31 | 0.5229 | 0.1336 | 0.0344 | 0.0547 | 0.8008 |
| No log | 2.0 | 62 | 0.3701 | 0.3628 | 0.3357 | 0.3487 | 0.8596 |
| No log | 3.0 | 93 | 0.3250 | 0.3979 | 0.4221 | 0.4097 | 0.8779 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 2.4.0
- Tokenizers 0.11.6