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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: bert-base-multilingual-cased
model-index:
- name: comic-name-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. -->

# comic-name-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: 0.0445
- Accuracy: 0.9937

## 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: 0.000125
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 25   | 0.0311          | 0.9933   |
| No log        | 2.0   | 50   | 0.0330          | 0.9937   |
| No log        | 3.0   | 75   | 0.0330          | 0.9933   |
| No log        | 4.0   | 100  | 0.0350          | 0.9941   |
| No log        | 5.0   | 125  | 0.0358          | 0.9937   |
| No log        | 6.0   | 150  | 0.0363          | 0.9937   |
| No log        | 7.0   | 175  | 0.0379          | 0.9945   |
| No log        | 8.0   | 200  | 0.0356          | 0.9941   |
| No log        | 9.0   | 225  | 0.0352          | 0.9941   |
| No log        | 10.0  | 250  | 0.0376          | 0.9941   |
| No log        | 11.0  | 275  | 0.0374          | 0.9941   |
| No log        | 12.0  | 300  | 0.0387          | 0.9937   |
| No log        | 13.0  | 325  | 0.0384          | 0.9941   |
| No log        | 14.0  | 350  | 0.0392          | 0.9941   |
| No log        | 15.0  | 375  | 0.0392          | 0.9941   |
| No log        | 16.0  | 400  | 0.0394          | 0.9941   |
| No log        | 17.0  | 425  | 0.0412          | 0.9945   |
| No log        | 18.0  | 450  | 0.0404          | 0.9941   |
| No log        | 19.0  | 475  | 0.0410          | 0.9941   |
| 0.0039        | 20.0  | 500  | 0.0414          | 0.9941   |
| 0.0039        | 21.0  | 525  | 0.0425          | 0.9941   |
| 0.0039        | 22.0  | 550  | 0.0416          | 0.9941   |
| 0.0039        | 23.0  | 575  | 0.0431          | 0.9941   |
| 0.0039        | 24.0  | 600  | 0.0439          | 0.9941   |
| 0.0039        | 25.0  | 625  | 0.0443          | 0.9941   |
| 0.0039        | 26.0  | 650  | 0.0440          | 0.9937   |
| 0.0039        | 27.0  | 675  | 0.0435          | 0.9937   |
| 0.0039        | 28.0  | 700  | 0.0428          | 0.9941   |
| 0.0039        | 29.0  | 725  | 0.0424          | 0.9941   |
| 0.0039        | 30.0  | 750  | 0.0431          | 0.9941   |
| 0.0039        | 31.0  | 775  | 0.0438          | 0.9941   |
| 0.0039        | 32.0  | 800  | 0.0419          | 0.9941   |
| 0.0039        | 33.0  | 825  | 0.0419          | 0.9941   |
| 0.0039        | 34.0  | 850  | 0.0416          | 0.9941   |
| 0.0039        | 35.0  | 875  | 0.0419          | 0.9941   |
| 0.0039        | 36.0  | 900  | 0.0430          | 0.9945   |
| 0.0039        | 37.0  | 925  | 0.0431          | 0.9941   |
| 0.0039        | 38.0  | 950  | 0.0439          | 0.9941   |
| 0.0039        | 39.0  | 975  | 0.0445          | 0.9937   |
| 0.0021        | 40.0  | 1000 | 0.0449          | 0.9937   |
| 0.0021        | 41.0  | 1025 | 0.0456          | 0.9941   |
| 0.0021        | 42.0  | 1050 | 0.0459          | 0.9941   |
| 0.0021        | 43.0  | 1075 | 0.0446          | 0.9937   |
| 0.0021        | 44.0  | 1100 | 0.0439          | 0.9941   |
| 0.0021        | 45.0  | 1125 | 0.0439          | 0.9941   |
| 0.0021        | 46.0  | 1150 | 0.0441          | 0.9941   |
| 0.0021        | 47.0  | 1175 | 0.0443          | 0.9941   |
| 0.0021        | 48.0  | 1200 | 0.0443          | 0.9937   |
| 0.0021        | 49.0  | 1225 | 0.0444          | 0.9937   |
| 0.0021        | 50.0  | 1250 | 0.0445          | 0.9937   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0