Lo logramos

README.md

@@ -2,14 +2,8 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
+- image-classification
 - generated_from_trainer
-metrics:
-- accuracy
-widget:
-- src: healthy.jpeg
-  example_title: Healthy
-- src: bean_rust.jpeg
-  example_title: Bean Rust
 model-index:
 - name: vit_model
   results: []
@@ -20,10 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit_model
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0777
-- Accuracy: 0.9774
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset.
 
 ## Model description
 
@@ -50,16 +41,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 4
 
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.1365        | 3.8462 | 500  | 0.0777          | 0.9774   |
-
-
 ### Framework versions
 
-- Transformers 4.40.1
+- Transformers 4.40.0
 - Pytorch 2.2.1+cu121
 - Datasets 2.19.0
 - Tokenizers 0.19.1

config.json

@@ -27,8 +27,7 @@
   "num_channels": 3,
   "num_hidden_layers": 12,
   "patch_size": 16,
-  "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.40.1"
+  "transformers_version": "4.40.0"
 }

model.safetensors

@@ -1,3 +1,3 @@
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 size 343227052

training_args.bin

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