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: 0.0453
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9857
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: 4.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 4 | 0.1549 | 0.0 | 0.0 | 0.0 | 0.9588 |
| No log | 2.0 | 8 | 0.1007 | 0.0 | 0.0 | 0.0 | 0.9588 |
| No log | 3.0 | 12 | 0.0592 | 0.0 | 0.0 | 0.0 | 0.9818 |
| No log | 4.0 | 16 | 0.0453 | 0.0 | 0.0 | 0.0 | 0.9857 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.10.1
- Datasets 2.6.1
- Tokenizers 0.13.1