metadata
library_name: transformers
license: mit
base_model: cjber/reddit-ner-place_names
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
- wer
model-index:
- name: reddit-ner-place_names-finetuned
results: []
reddit-ner-place_names-finetuned
This model is a fine-tuned version of cjber/reddit-ner-place_names on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0301
- Precision: 0.8010
- Recall: 0.8406
- F1: 0.8203
- Accuracy: 0.9929
- Wer: 0.0071
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 | Wer |
|---|---|---|---|---|---|---|---|---|
| 0.024 | 1.0 | 1535 | 0.0214 | 0.7826 | 0.8414 | 0.8109 | 0.9924 | 0.0075 |
| 0.0173 | 2.0 | 3070 | 0.0203 | 0.7865 | 0.8526 | 0.8182 | 0.9928 | 0.0072 |
| 0.0109 | 3.0 | 4605 | 0.0234 | 0.8166 | 0.8351 | 0.8257 | 0.9930 | 0.0070 |
| 0.0078 | 4.0 | 6140 | 0.0264 | 0.8179 | 0.8259 | 0.8219 | 0.9930 | 0.0070 |
| 0.005 | 5.0 | 7675 | 0.0301 | 0.8010 | 0.8406 | 0.8203 | 0.9929 | 0.0071 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1