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--- |
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base_model: EleutherAI/pythia-31m |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: BL-pythia-31m-simple_wikipedia_LM-2048 |
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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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# BL-pythia-31m-simple_wikipedia_LM-2048 |
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This model is a fine-tuned version of [EleutherAI/pythia-31m](https://huggingface.co/EleutherAI/pythia-31m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6874 |
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- Accuracy: 0.4105 |
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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: 0.0005 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 80085 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07 |
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- lr_scheduler_type: inverse_sqrt |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 3.0 |
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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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| 6.0657 | 0.22 | 100 | 5.6210 | 0.2414 | |
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| 5.2447 | 0.45 | 200 | 4.9316 | 0.3054 | |
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| 4.8397 | 0.67 | 300 | 4.6011 | 0.3343 | |
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| 4.7933 | 0.9 | 400 | 4.3878 | 0.3530 | |
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| 4.274 | 1.12 | 500 | 4.2352 | 0.3646 | |
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| 4.4867 | 1.35 | 600 | 4.1224 | 0.3723 | |
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| 4.3434 | 1.57 | 700 | 4.0282 | 0.3791 | |
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| 4.1857 | 1.8 | 800 | 3.9552 | 0.3841 | |
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| 4.229 | 2.02 | 900 | 3.8890 | 0.3909 | |
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| 3.9189 | 2.25 | 1000 | 3.8301 | 0.3967 | |
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| 4.084 | 2.47 | 1100 | 3.7782 | 0.4023 | |
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| 3.8965 | 2.7 | 1200 | 3.7302 | 0.4069 | |
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| 3.915 | 2.92 | 1300 | 3.6874 | 0.4105 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.2.0.dev20230907+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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