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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+morf_s0-30-x-2_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: 0.4329592727693433 |
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license: mit |
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language: |
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- en |
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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+morf_s0-30-x-2_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: 2.8423 |
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- Accuracy: 0.4330 |
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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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| 3.6569 | 0.03 | 10000 | 3.5764 | 0.3502 | |
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| 3.4317 | 0.06 | 20000 | 3.3581 | 0.3727 | |
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| 3.3161 | 0.09 | 30000 | 3.2447 | 0.3848 | |
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| 3.2463 | 0.13 | 40000 | 3.1761 | 0.3924 | |
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| 3.1897 | 0.16 | 50000 | 3.1277 | 0.3977 | |
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| 3.152 | 0.19 | 60000 | 3.0910 | 0.4022 | |
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| 3.1341 | 0.22 | 70000 | 3.0575 | 0.4060 | |
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| 3.1006 | 0.25 | 80000 | 3.0363 | 0.4084 | |
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| 3.0806 | 0.28 | 90000 | 3.0118 | 0.4115 | |
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| 3.0555 | 0.31 | 100000 | 2.9919 | 0.4138 | |
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| 3.038 | 0.34 | 110000 | 2.9786 | 0.4156 | |
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| 3.0291 | 0.38 | 120000 | 2.9651 | 0.4171 | |
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| 3.0182 | 0.41 | 130000 | 2.9499 | 0.4191 | |
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| 3.0145 | 0.44 | 140000 | 2.9381 | 0.4205 | |
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| 2.9891 | 0.47 | 150000 | 2.9272 | 0.4219 | |
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| 2.9836 | 0.5 | 160000 | 2.9191 | 0.4230 | |
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| 2.9717 | 0.53 | 170000 | 2.9103 | 0.4241 | |
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| 2.9651 | 0.56 | 180000 | 2.9039 | 0.4250 | |
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| 2.9615 | 0.59 | 190000 | 2.8971 | 0.4258 | |
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| 2.9556 | 0.63 | 200000 | 2.8882 | 0.4269 | |
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| 2.9452 | 0.66 | 210000 | 2.8825 | 0.4277 | |
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| 2.9412 | 0.69 | 220000 | 2.8766 | 0.4284 | |
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| 2.9402 | 0.72 | 230000 | 2.8722 | 0.4290 | |
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| 2.9299 | 0.75 | 240000 | 2.8675 | 0.4296 | |
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| 2.9302 | 0.78 | 250000 | 2.8623 | 0.4304 | |
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| 2.9165 | 0.81 | 260000 | 2.8585 | 0.4308 | |
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| 2.915 | 0.84 | 270000 | 2.8537 | 0.4314 | |
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| 2.92 | 0.88 | 280000 | 2.8506 | 0.4319 | |
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| 2.9186 | 0.91 | 290000 | 2.8484 | 0.4321 | |
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| 2.9084 | 0.94 | 300000 | 2.8458 | 0.4325 | |
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| 2.9142 | 0.97 | 310000 | 2.8438 | 0.4327 | |
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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 |
