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README.md
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---
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license: apache-2.0
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base_model: pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32
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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: PT-minipile-mega-small-2048-C1024-simplewiki-MR50-tk_ema32-MR0.50v2
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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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# PT-minipile-mega-small-2048-C1024-simplewiki-MR50-tk_ema32-MR0.50v2
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This model is a fine-tuned version of [pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32](https://huggingface.co/pszemraj/mega-small-2048-C1024-simplewiki-MR50-tk_ema32) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.7559
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- Accuracy: 0.4177
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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: 0.0002
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 3208
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.05
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- training_steps: 2000
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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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| 5.0539 | 0.05 | 100 | 5.0404 | 0.2907 |
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| 4.8869 | 0.1 | 200 | 4.6659 | 0.3216 |
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| 4.6364 | 0.15 | 300 | 4.4565 | 0.3416 |
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| 4.8682 | 0.2 | 400 | 4.3119 | 0.3557 |
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| 4.3904 | 0.25 | 500 | 4.2410 | 0.3664 |
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| 4.3191 | 0.3 | 600 | 4.1880 | 0.3701 |
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| 4.5587 | 0.35 | 700 | 4.0996 | 0.3789 |
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| 4.1517 | 0.4 | 800 | 4.0724 | 0.3839 |
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| 4.1427 | 0.45 | 900 | 4.0177 | 0.3892 |
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| 3.8845 | 0.5 | 1000 | 3.9725 | 0.3928 |
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| 4.1478 | 0.55 | 1100 | 3.9080 | 0.4007 |
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| 4.0271 | 0.6 | 1200 | 3.8979 | 0.4002 |
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| 4.0132 | 0.65 | 1300 | 3.8647 | 0.4057 |
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| 3.7284 | 0.7 | 1400 | 3.8518 | 0.4063 |
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| 3.9346 | 0.75 | 1500 | 3.8178 | 0.4100 |
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| 4.0403 | 0.8 | 1600 | 3.8015 | 0.4126 |
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| 3.9726 | 0.85 | 1700 | 3.7916 | 0.4138 |
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| 3.8489 | 0.9 | 1800 | 3.7630 | 0.4162 |
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| 3.7117 | 0.95 | 1900 | 3.7745 | 0.4162 |
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| 3.654 | 1.0 | 2000 | 3.7559 | 0.4177 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.1.0.dev20230809+cu121
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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