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Model: votaquangnhat/vietnamese-poem-gpt2-namchu
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: mit
+base_model: danghuy1999/gpt2-viwiki
+tags:
+- generated_from_trainer
+model-index:
+- name: vietnamese-poem-gpt2-namchu
+  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. -->
+
+# vietnamese-poem-gpt2-namchu
+
+This model is a fine-tuned version of [danghuy1999/gpt2-viwiki](https://huggingface.co/danghuy1999/gpt2-viwiki) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.2277
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 4.9894        | 1.0   | 2037  | 4.8025          |
+| 4.7181        | 2.0   | 4074  | 4.5903          |
+| 4.5653        | 3.0   | 6111  | 4.4569          |
+| 4.4342        | 4.0   | 8148  | 4.3877          |
+| 4.352         | 5.0   | 10185 | 4.3295          |
+| 4.307         | 6.0   | 12222 | 4.2892          |
+| 4.2481        | 7.0   | 14259 | 4.2575          |
+| 4.233         | 8.0   | 16296 | 4.2448          |
+| 4.2036        | 9.0   | 18333 | 4.2317          |
+| 4.18          | 10.0  | 20370 | 4.2277          |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0