metadata
license: mit
base_model: ukr-models/xlm-roberta-base-uk
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results: []
bert-finetuned-ner
This model is a fine-tuned version of ukr-models/xlm-roberta-base-uk on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6570
- Precision: 0.0917
- Recall: 0.5882
- F1: 0.1587
- Accuracy: 0.1101
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: 1
- eval_batch_size: 1
- 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 | 3 | 1.7579 | 0.0917 | 0.5882 | 0.1587 | 0.1101 |
| No log | 2.0 | 6 | 1.6570 | 0.0917 | 0.5882 | 0.1587 | 0.1101 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1