metadata
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
cfe-telmex-classification-finetuned-v2
This model is a fine-tuned version of 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