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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: ViT-GPT2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # ViT-GPT2
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.4134
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+ - Rouge2 Fmeasure: 0.1166
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 256
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Fmeasure |
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+ |:-------------:|:------:|:----:|:---------------:|:---------------:|
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+ | No log | 0.9987 | 496 | 2.4901 | 0.1077 |
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+ | 2.5089 | 1.9995 | 993 | 2.4292 | 0.1141 |
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+ | 2.4103 | 2.9962 | 1488 | 2.4134 | 0.1166 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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+ {
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+ "architectures": [
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+ "VisionEncoderDecoderModel"
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+ ],
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+ "_name_or_path": "gpt2",
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+ "activation_function": "gelu_new",
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+ "add_cross_attention": true,
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+ "architectures": [
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+ "GPT2LMHeadModel"
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+ ],
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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