metadata
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: []
bert-finetuned-protagonist-english-pc
This model is a fine-tuned version of 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