End of training

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-101
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: resnet-101-CivilEng11k_3Classes-new
+  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-101-CivilEng11k_3Classes-new
+
+This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.0001
+- eval_accuracy: 1.0
+- eval_runtime: 58.9592
+- eval_samples_per_second: 10.007
+- eval_steps_per_second: 0.322
+- epoch: 5.0
+- step: 140
+
+## 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: 0.0005
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- 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
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.0.1+cpu
+- Datasets 2.18.0
+- Tokenizers 0.15.1

all_results.json

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+{
+    "eval_accuracy": 1.0,
+    "eval_loss": 8.506989252055064e-05
+}

eval_results.json

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+{
+    "eval_accuracy": 1.0,
+    "eval_loss": 8.506989252055064e-05
+}

model.safetensors

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