|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: xlm-roberta-base-uk-base-ner |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# xlm-roberta-base-uk-base-ner |
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2510 |
|
- Precision: 0.5951 |
|
- Recall: 0.6256 |
|
- F1: 0.6100 |
|
- Accuracy: 0.9264 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.7224 | 1.0 | 514 | 0.3856 | 0.4590 | 0.4581 | 0.4586 | 0.8996 | |
|
| 0.3616 | 2.0 | 1028 | 0.2893 | 0.5528 | 0.5533 | 0.5531 | 0.9190 | |
|
| 0.2783 | 3.0 | 1542 | 0.2652 | 0.5661 | 0.5965 | 0.5809 | 0.9227 | |
|
| 0.2362 | 4.0 | 2056 | 0.2531 | 0.5882 | 0.6256 | 0.6063 | 0.9263 | |
|
| 0.2124 | 5.0 | 2570 | 0.2510 | 0.5951 | 0.6256 | 0.6100 | 0.9264 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
