initial commit

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- image-classification
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: tumour
+  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. -->
+
+# tumour
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the essam24/brain-tumour-v1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8286
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 1.0   | 195  | 4.5083          |
+| No log        | 2.0   | 390  | 1.4575          |
+| 3.0791        | 3.0   | 585  | 0.9050          |
+| 3.0791        | 4.0   | 780  | 0.8538          |
+| 3.0791        | 5.0   | 975  | 0.8286          |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 5.0,
+    "eval_loss": 0.8285718560218811,
+    "eval_runtime": 79.5915,
+    "eval_samples_per_second": 10.177,
+    "eval_steps_per_second": 0.641,
+    "total_flos": 3.588142521058099e+17,
+    "train_loss": 1.746917755909455,
+    "train_runtime": 2049.8226,
+    "train_samples_per_second": 7.584,
+    "train_steps_per_second": 0.476
+}

config.json

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+{
+  "_name_or_path": "microsoft/resnet-50",
+  "architectures": [
+    "ResNetForImageClassification"
+  ],
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsample_in_bottleneck": false,
+  "downsample_in_first_stage": false,
+  "embedding_size": 64,
+  "hidden_act": "relu",
+  "hidden_sizes": [
+    256,
+    512,
+    1024,
+    2048
+  ],
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "layer_type": "bottleneck",
+  "model_type": "resnet",
+  "num_channels": 3,
+  "out_features": [
+    "stage4"
+  ],
+  "out_indices": [
+    4
+  ],
+  "problem_type": "single_label_classification",
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4"
+}

eval_results.json

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+{
+    "epoch": 5.0,
+    "eval_loss": 0.8285718560218811,
+    "eval_runtime": 79.5915,
+    "eval_samples_per_second": 10.177,
+    "eval_steps_per_second": 0.641
+}

model.safetensors

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+size 102482856

train_results.json

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+{
+    "epoch": 5.0,
+    "total_flos": 3.588142521058099e+17,
+    "train_loss": 1.746917755909455,
+    "train_runtime": 2049.8226,
+    "train_samples_per_second": 7.584,
+    "train_steps_per_second": 0.476
+}

trainer_state.json

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+{
+  "best_metric": 0.8285718560218811,
+  "best_model_checkpoint": "./results/resnet/tumour/checkpoint-975",
+  "epoch": 5.0,
+  "eval_steps": 500,
+  "global_step": 975,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "eval_runtime": 77.3249,
+      "eval_samples_per_second": 10.475,
+      "eval_steps_per_second": 0.66,
+      "step": 195
+    },
+    {
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+      "eval_loss": 1.457480549812317,
+      "eval_runtime": 77.608,
+      "eval_samples_per_second": 10.437,
+      "eval_steps_per_second": 0.657,
+      "step": 390
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+    {
+      "epoch": 2.564102564102564,
+      "grad_norm": 205.6478729248047,
+      "learning_rate": 9.743589743589744e-06,
+      "loss": 3.0791,
+      "step": 500
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+    {
+      "epoch": 3.0,
+      "eval_loss": 0.9050098657608032,
+      "eval_runtime": 78.6283,
+      "eval_samples_per_second": 10.302,
+      "eval_steps_per_second": 0.649,
+      "step": 585
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+    {
+      "epoch": 4.0,
+      "eval_loss": 0.8538194298744202,
+      "eval_runtime": 79.9143,
+      "eval_samples_per_second": 10.136,
+      "eval_steps_per_second": 0.638,
+      "step": 780
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+    {
+      "epoch": 5.0,
+      "eval_loss": 0.8285718560218811,
+      "eval_runtime": 79.1036,
+      "eval_samples_per_second": 10.24,
+      "eval_steps_per_second": 0.645,
+      "step": 975
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+      "total_flos": 3.588142521058099e+17,
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+      "train_runtime": 2049.8226,
+      "train_samples_per_second": 7.584,
+      "train_steps_per_second": 0.476
+    }
+  ],
+  "logging_steps": 500,
+  "max_steps": 975,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 5,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 3.588142521058099e+17,
+  "train_batch_size": 16,
+  "trial_name": null,
+  "trial_params": null
+}

training_args.bin

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