---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ConcSeqBERT-Katchers
  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. -->

# ConcSeqBERT-Katchers

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4739
- Accuracy: 0.7904
- F1: 0.7903

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.4741        | 1.0   | 2522  | 0.4747          | 0.7773   | 0.7772 |
| 0.4248        | 2.0   | 5044  | 0.4739          | 0.7904   | 0.7903 |
| 0.3912        | 3.0   | 7566  | 0.5676          | 0.7838   | 0.7834 |
| 0.3674        | 4.0   | 10088 | 0.6120          | 0.7916   | 0.7915 |
| 0.3383        | 5.0   | 12610 | 0.7909          | 0.7907   | 0.7905 |
| 0.3303        | 6.0   | 15132 | 0.8127          | 0.7886   | 0.7885 |
| 0.3049        | 7.0   | 17654 | 0.9751          | 0.7890   | 0.7889 |
| 0.2488        | 8.0   | 20176 | 1.0986          | 0.7800   | 0.7799 |
| 0.2188        | 9.0   | 22698 | 1.1960          | 0.7762   | 0.7762 |
| 0.1971        | 10.0  | 25220 | 1.2763          | 0.7761   | 0.7761 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1