Upload README (1).md

README (1).md

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+---
+library_name: transformers
+base_model: motheecreator/ViT-GPT2-Image_Captioning_model
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+model-index:
+- name: ViT-GPT2
+  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-GPT2
+
+This model is a fine-tuned version of [motheecreator/ViT-GPT2-Image_Captioning_model](https://huggingface.co/motheecreator/ViT-GPT2-Image_Captioning_model) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.1879
+- Rouge2 Precision: None
+- Rouge2 Recall: None
+- Rouge2 Fmeasure: 0.1506
+- Bleu: 9.3133
+
+## 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: 8
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Bleu   |
+|:-------------:|:------:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|:------:|
+| 2.2959        | 0.9993 | 1171 | 2.2239          | None             | None          | 0.1474          | 8.9628 |
+| 2.1491        | 1.9985 | 2342 | 2.1879          | None             | None          | 0.1506          | 9.3133 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0
+- Datasets 3.0.0
+- Tokenizers 0.19.1