metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-finetuned-ner-S800
results: []
electra-finetuned-ner-S800
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0697
- Precision: 0.6146
- Recall: 0.7181
- F1: 0.6624
- Accuracy: 0.9758
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 | 55 | 0.1115 | 0.4736 | 0.5161 | 0.4940 | 0.9552 |
| No log | 2.0 | 110 | 0.0765 | 0.5789 | 0.6690 | 0.6207 | 0.9721 |
| No log | 3.0 | 165 | 0.0711 | 0.5671 | 0.7055 | 0.6288 | 0.9730 |
| No log | 4.0 | 220 | 0.0698 | 0.6266 | 0.7083 | 0.6649 | 0.9753 |
| No log | 5.0 | 275 | 0.0697 | 0.6146 | 0.7181 | 0.6624 | 0.9758 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3