tags: | |
- generated_from_trainer | |
metrics: | |
- precision | |
- recall | |
- f1 | |
- accuracy | |
base_model: Jean-Baptiste/roberta-large-ner-english | |
model-index: | |
- name: bert-finetuned-protagonist-english-pc | |
results: [] | |
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# bert-finetuned-protagonist-english-pc | |
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: 0.0351 | |
- Precision: 0.9513 | |
- Recall: 0.9598 | |
- F1: 0.9556 | |
- Accuracy: 0.9919 | |
## 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: 2 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| No log | 1.0 | 100 | 0.0407 | 0.9254 | 0.9420 | 0.9336 | 0.9908 | | |
| No log | 2.0 | 200 | 0.0351 | 0.9513 | 0.9598 | 0.9556 | 0.9919 | | |
### Framework versions | |
- Transformers 4.19.2 | |
- Pytorch 1.10.1+cu113 | |
- Datasets 2.2.1 | |
- Tokenizers 0.12.1 | |