metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-condaqa-neg-tag-token-classifier
results: []
roberta-large-condaqa-neg-tag-token-classifier
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0268
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9899
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: 256
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 0.1526 | 0.0 | 0.0 | 0.0 | 0.9588 |
| No log | 2.0 | 8 | 0.0875 | 0.0 | 0.0 | 0.0 | 0.9588 |
| No log | 3.0 | 12 | 0.0396 | 0.0 | 0.0 | 0.0 | 0.9877 |
| No log | 4.0 | 16 | 0.0322 | 0.0 | 0.0 | 0.0 | 0.9899 |
| No log | 5.0 | 20 | 0.0270 | 0.0 | 0.0 | 0.0 | 0.9906 |
| No log | 6.0 | 24 | 0.0268 | 0.0 | 0.0 | 0.0 | 0.9899 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.10.1
- Datasets 2.6.1
- Tokenizers 0.13.1