---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-ivrmenu-entity
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-ivrmenu-entity

This model is a fine-tuned version of [roberta-large](https://huggingface.co/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