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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- roneneldan/TinyStories |
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metrics: |
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- accuracy |
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model-index: |
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- name: gpt2_m080_tiny-stories_1024 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: roneneldan/TinyStories |
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type: roneneldan/TinyStories |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6787833469368093 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/scads-nlp/morph-gpt_gpt2_tiny-stories/runs/3tjo6ipp) |
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# gpt2_m080_tiny-stories_1024 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the roneneldan/TinyStories dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2099 |
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- Accuracy: 0.6788 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:| |
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| 2.8882 | 0.0522 | 1000 | 2.4481 | 0.4477 | |
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| 1.9734 | 0.1043 | 2000 | 1.7975 | 0.5687 | |
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| 1.7272 | 0.1565 | 3000 | 1.6134 | 0.6017 | |
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| 1.6087 | 0.2086 | 4000 | 1.5135 | 0.6195 | |
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| 1.5337 | 0.2608 | 5000 | 1.4512 | 0.6313 | |
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| 1.4808 | 0.3129 | 6000 | 1.4058 | 0.6399 | |
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| 1.444 | 0.3651 | 7000 | 1.3705 | 0.6466 | |
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| 1.4094 | 0.4173 | 8000 | 1.3408 | 0.6524 | |
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| 1.385 | 0.4694 | 9000 | 1.3191 | 0.6566 | |
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| 1.364 | 0.5216 | 10000 | 1.2988 | 0.6608 | |
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| 1.3413 | 0.5737 | 11000 | 1.2813 | 0.6643 | |
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| 1.3267 | 0.6259 | 12000 | 1.2677 | 0.6669 | |
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| 1.3161 | 0.6780 | 13000 | 1.2534 | 0.6697 | |
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| 1.3083 | 0.7302 | 14000 | 1.2439 | 0.6717 | |
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| 1.2955 | 0.7824 | 15000 | 1.2366 | 0.6731 | |
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| 1.285 | 0.8345 | 16000 | 1.2262 | 0.6754 | |
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| 1.2796 | 0.8867 | 17000 | 1.2194 | 0.6767 | |
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| 1.271 | 0.9388 | 18000 | 1.2133 | 0.6780 | |
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| 1.2678 | 0.9910 | 19000 | 1.2101 | 0.6787 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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