metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-neg-tags
results: []
roberta-large-neg-tags
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0016
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9997
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: 16
- 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 |
|---|---|---|---|---|---|---|---|
| 0.0143 | 1.0 | 938 | 0.0032 | 0.0 | 0.0 | 0.0 | 0.9995 |
| 0.0033 | 2.0 | 1876 | 0.0017 | 0.0 | 0.0 | 0.0 | 0.9996 |
| 0.0039 | 3.0 | 2814 | 0.0018 | 0.0 | 0.0 | 0.0 | 0.9997 |
| 0.0012 | 4.0 | 3752 | 0.0016 | 0.0 | 0.0 | 0.0 | 0.9997 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.10.1
- Datasets 2.6.1
- Tokenizers 0.13.1