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---
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language: pl
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tags:
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- generated_from_trainer
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- text-generation
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widget:
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- text: "Bolesław Leśmian - polski poeta"
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datasets:
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- wikipedia
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metrics:
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- accuracy
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model-index:
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- name: gpt_neo_pl_125M
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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: wikipedia 20220720.pl
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type: wikipedia
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args: 20220720.pl
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.4312838299951148
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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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# gpt_neo_pl_125M_v2
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This model was trained from scratch on the wikipedia 20220720.pl dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.3862
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- Accuracy: 0.4313
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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: 1
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 1000
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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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| 5.9469 | 0.02 | 1000 | 6.5843 | 0.1435 |
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| 4.9953 | 0.05 | 2000 | 5.7709 | 0.1911 |
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| 4.3754 | 0.07 | 3000 | 5.2624 | 0.2331 |
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| 3.9795 | 0.1 | 4000 | 4.8752 | 0.2731 |
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| 3.7099 | 0.12 | 5000 | 4.5927 | 0.3039 |
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| 3.4747 | 0.15 | 6000 | 4.3942 | 0.3230 |
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| 3.343 | 0.17 | 7000 | 4.2879 | 0.3349 |
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| 3.2767 | 0.2 | 8000 | 4.1698 | 0.3459 |
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| 3.1852 | 0.22 | 9000 | 4.0925 | 0.3534 |
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| 3.0871 | 0.25 | 10000 | 4.0239 | 0.3608 |
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| 3.0746 | 0.27 | 11000 | 3.9646 | 0.3664 |
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| 2.9473 | 0.3 | 12000 | 3.9245 | 0.3706 |
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| 2.9737 | 0.32 | 13000 | 3.8742 | 0.3754 |
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| 2.9193 | 0.35 | 14000 | 3.8285 | 0.3796 |
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| 2.8833 | 0.37 | 15000 | 3.7952 | 0.3837 |
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| 2.8533 | 0.4 | 16000 | 3.7616 | 0.3873 |
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| 2.8654 | 0.42 | 17000 | 3.7296 | 0.3907 |
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| 2.8196 | 0.44 | 18000 | 3.7049 | 0.3936 |
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| 2.7883 | 0.47 | 19000 | 3.6786 | 0.3966 |
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| 2.747 | 0.49 | 20000 | 3.6488 | 0.3990 |
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| 2.7355 | 0.52 | 21000 | 3.6243 | 0.4021 |
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| 2.7355 | 0.54 | 22000 | 3.5982 | 0.4053 |
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| 2.6999 | 0.57 | 23000 | 3.5765 | 0.4075 |
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| 2.7243 | 0.59 | 24000 | 3.5558 | 0.4101 |
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| 2.6526 | 0.62 | 25000 | 3.5371 | 0.4125 |
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| 2.641 | 0.64 | 26000 | 3.5150 | 0.4146 |
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| 2.6602 | 0.67 | 27000 | 3.4971 | 0.4168 |
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| 2.644 | 0.69 | 28000 | 3.4812 | 0.4192 |
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| 2.6558 | 0.72 | 29000 | 3.4622 | 0.4215 |
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| 2.5664 | 0.74 | 30000 | 3.4504 | 0.4229 |
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| 2.5669 | 0.77 | 31000 | 3.4376 | 0.4245 |
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| 2.5498 | 0.79 | 32000 | 3.4263 | 0.4263 |
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| 2.5874 | 0.82 | 33000 | 3.4169 | 0.4274 |
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| 2.5555 | 0.84 | 34000 | 3.4067 | 0.4286 |
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| 2.5502 | 0.86 | 35000 | 3.3997 | 0.4298 |
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| 2.5232 | 0.89 | 36000 | 3.3946 | 0.4302 |
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| 2.5369 | 0.91 | 37000 | 3.3898 | 0.4309 |
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| 2.5335 | 0.94 | 38000 | 3.3869 | 0.4313 |
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| 2.6032 | 0.96 | 39000 | 3.3853 | 0.4315 |
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| 2.5244 | 0.99 | 40000 | 3.3850 | 0.4314 |
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### Framework versions
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- Transformers 4.22.0.dev0
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- Pytorch 1.12.0
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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