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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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- uonlp/CulturaX |
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metrics: |
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- accuracy |
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model-index: |
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- name: gpt2_cx-en_00000-00009_50k |
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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: uonlp/CulturaX en |
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type: uonlp/CulturaX |
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args: en |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.36165373273858764 |
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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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# gpt2_cx-en_00000-00009_50k |
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This model is a fine-tuned version of [](https://huggingface.co/) on the uonlp/CulturaX en dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5834 |
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- Accuracy: 0.3617 |
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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: 64 |
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- eval_batch_size: 64 |
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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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| 4.586 | 0.04 | 10000 | 4.4977 | 0.2821 | |
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| 4.2706 | 0.08 | 20000 | 4.1928 | 0.3058 | |
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| 4.1189 | 0.12 | 30000 | 4.0469 | 0.3179 | |
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| 4.0314 | 0.16 | 40000 | 3.9610 | 0.3253 | |
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| 3.9704 | 0.2 | 50000 | 3.8977 | 0.3311 | |
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| 3.923 | 0.24 | 60000 | 3.8486 | 0.3353 | |
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| 3.888 | 0.28 | 70000 | 3.8084 | 0.3390 | |
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| 3.8529 | 0.32 | 80000 | 3.7777 | 0.3423 | |
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| 3.832 | 0.36 | 90000 | 3.7526 | 0.3446 | |
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| 3.8102 | 0.4 | 100000 | 3.7277 | 0.3470 | |
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| 3.7876 | 0.44 | 110000 | 3.7073 | 0.3490 | |
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| 3.7686 | 0.48 | 120000 | 3.6922 | 0.3506 | |
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| 3.7585 | 0.52 | 130000 | 3.6750 | 0.3522 | |
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| 3.7459 | 0.56 | 140000 | 3.6620 | 0.3535 | |
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| 3.7378 | 0.6 | 150000 | 3.6501 | 0.3545 | |
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| 3.7181 | 0.64 | 160000 | 3.6385 | 0.3559 | |
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| 3.7139 | 0.68 | 170000 | 3.6293 | 0.3568 | |
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| 3.6958 | 0.72 | 180000 | 3.6201 | 0.3578 | |
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| 3.6872 | 0.76 | 190000 | 3.6122 | 0.3585 | |
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| 3.6888 | 0.8 | 200000 | 3.6060 | 0.3592 | |
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| 3.6765 | 0.84 | 210000 | 3.6001 | 0.3599 | |
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| 3.6734 | 0.88 | 220000 | 3.5945 | 0.3604 | |
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| 3.6669 | 0.92 | 230000 | 3.5891 | 0.3611 | |
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| 3.6696 | 0.96 | 240000 | 3.5856 | 0.3614 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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