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End of training
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README.md
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---
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license: mit
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base_model: VietAI/vit5-base
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: mymodel_LORA_base_10k_2e5_3epoch_batch16_T4
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results: []
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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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# mymodel_LORA_base_10k_2e5_3epoch_batch16_T4
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This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9509
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- Rouge1: 0.5087
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- Rouge2: 0.21
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- Rougel: 0.3279
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- Rougelsum: 0.3278
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- Gen Len: 47.1885
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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| 2.904 | 1.0 | 500 | 2.0384 | 0.4986 | 0.1981 | 0.323 | 0.3231 | 54.0445 |
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| 2.167 | 2.0 | 1000 | 1.9662 | 0.5068 | 0.2053 | 0.3269 | 0.3268 | 54.8295 |
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| 2.1217 | 3.0 | 1500 | 1.9509 | 0.5087 | 0.21 | 0.3279 | 0.3278 | 47.1885 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.7
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- Tokenizers 0.14.1
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