metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-ivrmenu-entity
results: []
roberta-ivrmenu-entity
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.8282
- Recall: 0.8911
- F1: 0.8585
- Accuracy: 0.9345
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 2 | nan | 0.9036 | 0.4950 | 0.6397 | 0.6503 |
| No log | 2.0 | 4 | nan | 0.5952 | 0.5776 | 0.5863 | 0.7387 |
| No log | 3.0 | 6 | nan | 0.7124 | 0.7030 | 0.7076 | 0.8232 |
| No log | 4.0 | 8 | nan | 0.6879 | 0.7492 | 0.7172 | 0.8402 |
| No log | 5.0 | 10 | nan | 0.7333 | 0.7987 | 0.7646 | 0.8880 |
| No log | 6.0 | 12 | nan | 0.7462 | 0.8152 | 0.7792 | 0.9044 |
| No log | 7.0 | 14 | nan | 0.7761 | 0.8350 | 0.8045 | 0.9142 |
| No log | 8.0 | 16 | nan | 0.8145 | 0.8548 | 0.8341 | 0.9247 |
| No log | 9.0 | 18 | nan | 0.8185 | 0.8779 | 0.8471 | 0.9306 |
| No log | 10.0 | 20 | nan | 0.8282 | 0.8911 | 0.8585 | 0.9345 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.12.1