metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: 8Agos
results: []
roberta_finetuned_astronomicalNER
This model is a fine-tuned version of xlm-roberta-large-finetuned-conll03-english on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1416
- Precision: 0.7659
- Recall: 0.7986
- F1: 0.7819
- Accuracy: 0.9640
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 176 | 0.1571 | 0.7362 | 0.7788 | 0.7569 | 0.9593 |
| No log | 2.0 | 352 | 0.1416 | 0.7529 | 0.7831 | 0.7677 | 0.9624 |
| 0.1109 | 3.0 | 528 | 0.1416 | 0.7659 | 0.7986 | 0.7819 | 0.9640 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1