---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cfe-telmex-classification-finetuned-v2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: JoseVilla--cfe_telmex_classification_v1
      split: train
      args: JoseVilla--cfe_telmex_classification_v1
    metrics:
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# cfe-telmex-classification-finetuned-v2

This model is a fine-tuned version of [JoseVilla/cfe-telmex-classification-finetuned-v1](https://huggingface.co/JoseVilla/cfe-telmex-classification-finetuned-v1) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1568
- Accuracy: 1.0

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 0.3749          | 0.7586   |
| No log        | 2.0   | 4    | 0.1568          | 1.0      |
| No log        | 3.0   | 6    | 0.0495          | 1.0      |
| No log        | 4.0   | 8    | 0.0188          | 1.0      |
| 0.136         | 5.0   | 10   | 0.0087          | 1.0      |
| 0.136         | 6.0   | 12   | 0.0060          | 1.0      |
| 0.136         | 7.0   | 14   | 0.0063          | 1.0      |
| 0.136         | 8.0   | 16   | 0.0039          | 1.0      |
| 0.136         | 9.0   | 18   | 0.0018          | 1.0      |
| 0.0129        | 10.0  | 20   | 0.0015          | 1.0      |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3