metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: german-english-binary-ner-roberta-base-30-final
results: []
german-english-binary-ner-roberta-base-30-final
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1571
- Precision: 0.7113
- Recall: 0.8042
- F1: 0.7549
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: 1e-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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 2.36 | 250 | 0.0813 | 0.6063 | 0.7778 | 0.6814 |
| 0.0606 | 4.72 | 500 | 0.0871 | 0.6745 | 0.8290 | 0.7438 |
| 0.0606 | 7.08 | 750 | 0.1051 | 0.7218 | 0.7746 | 0.7473 |
| 0.0099 | 9.43 | 1000 | 0.1103 | 0.7428 | 0.7628 | 0.7527 |
| 0.0099 | 11.79 | 1250 | 0.1156 | 0.7349 | 0.7843 | 0.7588 |
| 0.0037 | 14.15 | 1500 | 0.1200 | 0.7323 | 0.7881 | 0.7592 |
| 0.0037 | 16.51 | 1750 | 0.1415 | 0.7139 | 0.7977 | 0.7535 |
| 0.0018 | 18.87 | 2000 | 0.1339 | 0.7218 | 0.7880 | 0.7534 |
| 0.0018 | 21.23 | 2250 | 0.1423 | 0.7533 | 0.7820 | 0.7674 |
| 0.001 | 23.58 | 2500 | 0.1506 | 0.7192 | 0.7806 | 0.7486 |
| 0.001 | 25.94 | 2750 | 0.1521 | 0.7165 | 0.8077 | 0.7594 |
| 0.0006 | 28.3 | 3000 | 0.1571 | 0.7113 | 0.8042 | 0.7549 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0