metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-NER-crypto
results: []
xlm-roberta-base-finetuned-NER-crypto
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0058
- F1: 0.9970
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: 5e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0269 | 1.0 | 750 | 0.0080 | 0.9957 |
| 0.0049 | 2.0 | 1500 | 0.0074 | 0.9960 |
| 0.0042 | 3.0 | 2250 | 0.0074 | 0.9965 |
| 0.0034 | 4.0 | 3000 | 0.0058 | 0.9971 |
| 0.0028 | 5.0 | 3750 | 0.0059 | 0.9971 |
| 0.0024 | 6.0 | 4500 | 0.0058 | 0.9970 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1