metadata
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test-ner
test-ner
This model was trained from scratch on an unkown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4357
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8863
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: 0.02
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 340 | 0.4357 | 0.0 | 0.0 | 0.0 | 0.8863 |
Framework versions
- Transformers 4.6.1
- Pytorch 1.9.0
- Datasets 1.6.2
- Tokenizers 0.10.3