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--- |
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license: apache-2.0 |
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base_model: distilbert/distilgpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: tiny-gpt2-br |
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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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# tiny-gpt2-br |
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This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co./distilbert/distilgpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6959 |
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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: 0.0004 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 5.966 | 0.21 | 1000 | 5.0526 | |
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| 4.8376 | 0.42 | 2000 | 4.6063 | |
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| 4.5265 | 0.63 | 3000 | 4.3822 | |
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| 4.3549 | 0.84 | 4000 | 4.2353 | |
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| 4.1914 | 1.05 | 5000 | 4.1234 | |
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| 3.9985 | 1.26 | 6000 | 4.0512 | |
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| 3.9496 | 1.47 | 7000 | 3.9737 | |
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| 3.9029 | 1.68 | 8000 | 3.9040 | |
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| 3.8636 | 1.89 | 9000 | 3.8523 | |
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| 3.7011 | 2.1 | 10000 | 3.8414 | |
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| 3.5776 | 2.31 | 11000 | 3.8034 | |
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| 3.5683 | 2.52 | 12000 | 3.7755 | |
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| 3.5686 | 2.73 | 13000 | 3.7375 | |
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| 3.5352 | 2.94 | 14000 | 3.7042 | |
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| 3.3404 | 3.15 | 15000 | 3.7406 | |
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| 3.2763 | 3.36 | 16000 | 3.7177 | |
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| 3.2792 | 3.56 | 17000 | 3.7004 | |
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| 3.2808 | 3.77 | 18000 | 3.6864 | |
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| 3.2816 | 3.98 | 19000 | 3.6639 | |
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| 3.0586 | 4.19 | 20000 | 3.7184 | |
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| 3.0485 | 4.4 | 21000 | 3.7085 | |
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| 3.0446 | 4.61 | 22000 | 3.7014 | |
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| 3.0407 | 4.82 | 23000 | 3.6959 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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