update model card README.md

README.md

@@ -0,0 +1,86 @@
+---
+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
+should probably proofread and complete it, then remove this comment. -->
+
+# 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: 0.0015
+- 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