metadata
license: apache-2.0
base_model: JoseVilla/cfe-telmex-classification-finetuned-v2
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cfe-telmex-classification-finetuned-v3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9583333333333334
cfe-telmex-classification-finetuned-v3
This model is a fine-tuned version of JoseVilla/cfe-telmex-classification-finetuned-v2 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2047
- Accuracy: 0.9583
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.94 | 8 | 0.4386 | 0.8167 |
0.6716 | 2.0 | 17 | 0.2047 | 0.9583 |
0.1864 | 2.82 | 24 | 0.1664 | 0.9583 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3