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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: results |
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results: [] |
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language: |
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- en |
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metrics: |
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- accuracy |
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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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# Results |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the Kubernetes dataset, which is updated in the same hub! |
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## Model description |
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This model can be used to generate texts related to Kubernetes. |
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This would be the first model towards interests in IBN. |
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## Intended uses & limitations |
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It can be used for the text generation. |
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## Training and evaluation data |
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This model contains only the training data and no evaluation data. |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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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: |
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TrainOutput(global_step=3, training_loss=3.4602108001708984, metrics={'train_runtime': 83.5107, 'train_samples_per_second': 0.036, 'train_steps_per_second': 0.036, 'total_flos': 1567752192000.0, 'train_loss': 3.4602108001708984, 'epoch': 3.0}) |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
