---
library_name: transformers
license: apache-2.0
base_model: amberoad/bert-multilingual-passage-reranking-msmarco
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category_predictor
  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. -->

# category_predictor

This model is a fine-tuned version of [amberoad/bert-multilingual-passage-reranking-msmarco](https://huggingface.co/amberoad/bert-multilingual-passage-reranking-msmarco) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9181
- Accuracy: 0.8626

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.9646        | 1.0   | 152248 | 1.3476          | 0.7807   |
| 0.611         | 2.0   | 304496 | 1.0336          | 0.8401   |
| 0.4423        | 3.0   | 456744 | 0.9181          | 0.8626   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3