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---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-protagonist-english
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. -->
# bert-finetuned-protagonist-english
This model is a fine-tuned version of [Jean-Baptiste/roberta-large-ner-english](https://huggingface.co/Jean-Baptiste/roberta-large-ner-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0630
- Precision: 0.8646
- Recall: 0.8839
- F1: 0.8742
- Accuracy: 0.9876
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 25 | 0.0659 | 0.8860 | 0.9018 | 0.8938 | 0.9862 |
| No log | 2.0 | 50 | 0.0583 | 0.8553 | 0.8705 | 0.8628 | 0.9860 |
| No log | 3.0 | 75 | 0.0593 | 0.8728 | 0.8884 | 0.8805 | 0.9876 |
| No log | 4.0 | 100 | 0.0622 | 0.8559 | 0.875 | 0.8653 | 0.9871 |
| No log | 5.0 | 125 | 0.0630 | 0.8646 | 0.8839 | 0.8742 | 0.9876 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.10.2+cu102
- Datasets 2.2.1
- Tokenizers 0.11.0
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