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tringuyen-uit
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ER_new_context

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  1. README.md +87 -0
  2. model.safetensors +1 -1
  3. runs/May28_02-58-58_87292875f7cd/events.out.tfevents.1716865140.87292875f7cd.24.0 +2 -2
README.md ADDED
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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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+ model-index:
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+ - name: ER_new_context
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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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+ # ER_new_context
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+
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+ This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4057
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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: 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.2979 | 0.1 | 100 | 1.2437 |
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+ | 1.1026 | 0.19 | 200 | 0.7365 |
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+ | 0.7482 | 0.29 | 300 | 0.5781 |
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+ | 0.6258 | 0.38 | 400 | 0.5159 |
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+ | 0.5153 | 0.48 | 500 | 0.4504 |
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+ | 0.4802 | 0.57 | 600 | 0.4455 |
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+ | 0.4905 | 0.67 | 700 | 0.4059 |
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+ | 0.382 | 0.76 | 800 | 0.4778 |
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+ | 0.3728 | 0.86 | 900 | 0.3985 |
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+ | 0.3274 | 0.96 | 1000 | 0.3982 |
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+ | 0.3639 | 1.05 | 1100 | 0.4184 |
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+ | 0.2881 | 1.15 | 1200 | 0.4454 |
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+ | 0.3194 | 1.24 | 1300 | 0.3778 |
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+ | 0.2695 | 1.34 | 1400 | 0.3957 |
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+ | 0.2894 | 1.43 | 1500 | 0.4000 |
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+ | 0.276 | 1.53 | 1600 | 0.3984 |
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+ | 0.2325 | 1.62 | 1700 | 0.3627 |
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+ | 0.2192 | 1.72 | 1800 | 0.3782 |
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+ | 0.279 | 1.81 | 1900 | 0.4161 |
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+ | 0.2636 | 1.91 | 2000 | 0.4026 |
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+ | 0.2932 | 2.01 | 2100 | 0.3232 |
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+ | 0.206 | 2.1 | 2200 | 0.3633 |
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+ | 0.1865 | 2.2 | 2300 | 0.4019 |
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+ | 0.1651 | 2.29 | 2400 | 0.4385 |
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+ | 0.167 | 2.39 | 2500 | 0.4277 |
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+ | 0.1705 | 2.48 | 2600 | 0.4083 |
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+ | 0.2321 | 2.58 | 2700 | 0.3667 |
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+ | 0.1912 | 2.67 | 2800 | 0.3772 |
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+ | 0.192 | 2.77 | 2900 | 0.4032 |
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+ | 0.1881 | 2.87 | 3000 | 0.4059 |
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+ | 0.152 | 2.96 | 3100 | 0.4057 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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