Model save

README.md

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+---
+base_model: microsoft/dit-base-finetuned-rvlcdip
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: dit-base-rvlcdip-finetuned-grp-actual
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7575757575757576
+---
+
+<!-- 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. -->
+
+# dit-base-rvlcdip-finetuned-grp-actual
+
+This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2240
+- Accuracy: 0.7576
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.3577        | 0.96  | 18   | 2.0863          | 0.5114   |
+| 2.0601        | 1.97  | 37   | 1.8154          | 0.6477   |
+| 1.8068        | 2.99  | 56   | 1.5881          | 0.6705   |
+| 1.5953        | 4.0   | 75   | 1.4112          | 0.7159   |
+| 1.4304        | 4.96  | 93   | 1.3033          | 0.7576   |
+| 1.3458        | 5.97  | 112  | 1.2401          | 0.75     |
+| 1.3523        | 6.72  | 126  | 1.2240          | 0.7576   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

pytorch_model.bin

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