update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+model-index:
+- name: vit-fire-detection
+  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. -->
+
+# vit-fire-detection
+
+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 None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0259
+- Precision: 0.9947
+- Recall: 0.9947
+
+## 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: 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_steps: 100
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.1186        | 1.0   | 190  | 0.0757          | 0.9789    | 0.9775 |
+| 0.0392        | 2.0   | 380  | 0.0259          | 0.9947    | 0.9947 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.14.0.dev20221111
+- Datasets 2.8.0
+- Tokenizers 0.12.1