Thamer
/

resnet-fine_tuned

@@ -1,206 +1,77 @@
 ---
-datasets:
-- Falah/Alzheimer_MRI
-language:
-- en
 metrics:
 - accuracy
-library_name: transformers
-pipeline_tag: image-classification
-license: apache-2.0
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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 ---
+license: apache-2.0
+base_model: microsoft/resnet-34
+tags:
+- generated_from_trainer
 metrics:
 - accuracy
+model-index:
+- name: resnet-fine_tuned
+  results: []
 ---
+<!-- 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. -->
+# resnet-fine_tuned
+This model is a fine-tuned version of [microsoft/resnet-34](https://huggingface.co/microsoft/resnet-34) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1983
+- Accuracy: 0.9219
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9041        | 1.0   | 80   | 0.9659          | 0.5352   |
+| 0.8743        | 2.0   | 160  | 0.9348          | 0.5797   |
+| 0.7723        | 3.0   | 240  | 0.7793          | 0.6594   |
+| 0.6864        | 4.0   | 320  | 0.6799          | 0.7031   |
+| 0.5347        | 5.0   | 400  | 0.5596          | 0.7703   |
+| 0.4282        | 6.0   | 480  | 0.5078          | 0.7766   |
+| 0.4315        | 7.0   | 560  | 0.5455          | 0.7680   |
+| 0.3747        | 8.0   | 640  | 0.4203          | 0.8266   |
+| 0.2977        | 9.0   | 720  | 0.3926          | 0.8469   |
+| 0.2252        | 10.0  | 800  | 0.3024          | 0.8742   |
+| 0.2675        | 11.0  | 880  | 0.2731          | 0.8906   |
+| 0.2136        | 12.0  | 960  | 0.3045          | 0.875    |
+| 0.1998        | 13.0  | 1040 | 0.2370          | 0.9      |
+| 0.2406        | 14.0  | 1120 | 0.2387          | 0.9086   |
+| 0.1873        | 15.0  | 1200 | 0.1983          | 0.9219   |
+### Framework versions
+- Transformers 4.31.0
+- Pytorch 2.0.1+cpu
+- Datasets 2.13.1
+- Tokenizers 0.13.3