metadata
library_name: transformers
license: cc-by-4.0
base_model: pczarnik/herbert-base-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: herbert-ner-finetuned
results: []
herbert-ner-finetuned
This model is a fine-tuned version of pczarnik/herbert-base-ner on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0014
- Precision: 0.9977
- Recall: 0.9982
- F1: 0.9980
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 327
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| 0.0072 | 0.7634 | 500 | 0.0061 | 0.9697 | 0.9905 | 0.98 |
| 0.0034 | 1.5267 | 1000 | 0.0031 | 0.9879 | 0.9960 | 0.9920 |
| 0.0016 | 2.2901 | 1500 | 0.0017 | 0.9958 | 0.9980 | 0.9969 |
| 0.0012 | 3.0534 | 2000 | 0.0017 | 0.9958 | 0.9975 | 0.9966 |
| 0.0007 | 3.8168 | 2500 | 0.0015 | 0.9976 | 0.9983 | 0.9980 |
| 0.0004 | 4.5802 | 3000 | 0.0015 | 0.9976 | 0.9977 | 0.9977 |
| 0.0006 | 5.3435 | 3500 | 0.0014 | 0.9977 | 0.9982 | 0.9980 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.19.1