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---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 16class_all9k_promptcorr_tweet_300other_23nov23_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_all9k_promptcorr_tweet_300other_23nov23_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: 0.0267
- Accuracy: 0.9947

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5225        | 1.0   | 721  | 0.6075          | 0.8344   |
| 0.7164        | 2.0   | 1442 | 0.3430          | 0.9051   |
| 0.3828        | 3.0   | 2163 | 0.2532          | 0.9271   |
| 0.318         | 4.0   | 2884 | 0.1631          | 0.9572   |
| 0.2131        | 5.0   | 3605 | 0.1231          | 0.9676   |
| 0.1728        | 6.0   | 4326 | 0.0822          | 0.9807   |
| 0.1344        | 7.0   | 5047 | 0.0657          | 0.9849   |
| 0.0902        | 8.0   | 5768 | 0.0471          | 0.9887   |
| 0.0842        | 9.0   | 6489 | 0.0383          | 0.9912   |
| 0.0609        | 10.0  | 7210 | 0.0281          | 0.9941   |
| 0.0512        | 11.0  | 7931 | 0.0267          | 0.9947   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0