---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16class_combo_vth_new_pp_full_updated_tweet_13nov23_v1
  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. -->

# 16class_combo_vth_new_pp_full_updated_tweet_13nov23_v1

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: 0.0420
- Accuracy: 0.9908

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 11

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5945        | 1.0   | 735  | 0.7331          | 0.7813   |
| 0.8273        | 2.0   | 1470 | 0.4370          | 0.8743   |
| 0.4943        | 3.0   | 2205 | 0.3176          | 0.9061   |
| 0.3995        | 4.0   | 2940 | 0.2252          | 0.9335   |
| 0.2712        | 5.0   | 3675 | 0.1714          | 0.9517   |
| 0.2352        | 6.0   | 4410 | 0.1183          | 0.9690   |
| 0.1794        | 7.0   | 5145 | 0.0823          | 0.9795   |
| 0.1361        | 8.0   | 5880 | 0.0634          | 0.9861   |
| 0.1111        | 9.0   | 6615 | 0.0514          | 0.9885   |
| 0.0891        | 10.0  | 7350 | 0.0440          | 0.9900   |
| 0.0675        | 11.0  | 8085 | 0.0420          | 0.9908   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1