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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilgpt2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- benchaffe/shakespeare-lines |
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language: |
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- en |
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metrics: |
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- perplexity |
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pipeline_tag: text-generation |
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model-index: |
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- name: shakespeare-distilgpt2 |
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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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# shakespeare-distilgpt2 |
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This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on the [shakespeare-lines](https://huggingface.co/benchaffe/shakespeare-lines) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.2490 |
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- Perplexity: 74.01 |
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## Training and evaluation data |
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The training and evaluation data was taken from the [shakespeare-lines](https://huggingface.co/benchaffe/shakespeare-lines) dataset. The dataset was shuffled with a seed of 24, and split into training and evaluation with a ratio of 80:20. |
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## Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("benchaffe/shakespeare-distilgpt2") |
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tokenizer = AutoTokenizer.from_pretrained("benchaffe/shakespeare-distilgpt2") |
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prompt = "What light through yonder window breaks" |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate( |
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**inputs, |
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max_length=80, |
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temperature=0.8, |
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top_p=0.95, |
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do_sample=True |
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) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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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: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 3.9479 | 1.0 | 22941 | 4.2781 | |
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| 3.7527 | 2.0 | 45882 | 4.2111 | |
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| 3.5778 | 3.0 | 68823 | 4.2035 | |
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| 3.4214 | 4.0 | 91764 | 4.2129 | |
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| 3.3513 | 5.0 | 114705 | 4.2490 | |
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### Framework versions |
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- Transformers 4.52.4 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
