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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lyfi-expert-classification
  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. -->

# lyfi-expert-classification

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0583        | 0.25  | 500  | 0.0002          | 1.0      |
| 0.0002        | 0.5   | 1000 | 0.0001          | 1.0      |
| 0.0001        | 0.75  | 1500 | 0.0000          | 1.0      |
| 0.0           | 1.0   | 2000 | 0.0000          | 1.0      |
| 0.0           | 1.25  | 2500 | 0.0000          | 1.0      |
| 0.0           | 1.5   | 3000 | 0.0000          | 1.0      |
| 0.0           | 1.75  | 3500 | 0.0000          | 1.0      |
| 0.0           | 2.0   | 4000 | 0.0000          | 1.0      |
| 0.0           | 2.25  | 4500 | 0.0000          | 1.0      |
| 0.0           | 2.5   | 5000 | 0.0000          | 1.0      |
| 0.0           | 2.75  | 5500 | 0.0000          | 1.0      |
| 0.0           | 3.0   | 6000 | 0.0000          | 1.0      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.3.0.dev20240212
- Datasets 2.16.1
- Tokenizers 0.15.0