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--- |
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license: mit |
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base_model: xlnet-base-cased |
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tags: |
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- Text Generation |
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- generated_from_trainer |
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model-index: |
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- name: xLNet-finetuned-cXg-nl-to-code |
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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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# xLNet-finetuned-cXg-nl-to-code |
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 20.6526 |
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- eval_rouge1: 0.0685 |
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- eval_rouge2: 0.0062 |
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- eval_rougeL: 0.0550 |
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- eval_bleu: 0.8352 |
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- eval_meteor: 0.1311 |
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- eval_codebleu: 0.2193 |
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- eval_runtime: 265.1606 |
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- eval_samples_per_second: 0.038 |
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- eval_steps_per_second: 0.004 |
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- step: 0 |
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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: 32 |
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- eval_batch_size: 64 |
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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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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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