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--- |
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license: mit |
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base_model: gpt2-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: tiq |
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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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# tiq |
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This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.5477 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 6.2342 | 0.04 | 100 | 6.1857 | |
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| 5.7599 | 0.07 | 200 | 5.7751 | |
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| 5.7433 | 0.11 | 300 | 5.7142 | |
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| 5.6021 | 0.15 | 400 | 5.6776 | |
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| 5.5084 | 0.18 | 500 | 5.6349 | |
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| 5.3825 | 0.22 | 600 | 5.6201 | |
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| 5.6698 | 0.26 | 700 | 5.5831 | |
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| 5.4089 | 0.29 | 800 | 5.5687 | |
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| 5.601 | 0.33 | 900 | 5.5574 | |
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| 5.4708 | 0.37 | 1000 | 5.5555 | |
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| 5.5956 | 0.4 | 1100 | 5.5520 | |
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| 5.4704 | 0.44 | 1200 | 5.5494 | |
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| 5.4824 | 0.47 | 1300 | 5.5502 | |
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| 5.589 | 0.51 | 1400 | 5.5478 | |
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| 5.5612 | 0.55 | 1500 | 5.5456 | |
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| 5.4741 | 0.58 | 1600 | 5.5430 | |
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| 5.463 | 0.62 | 1700 | 5.5426 | |
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| 5.5071 | 0.66 | 1800 | 5.5424 | |
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| 5.5469 | 0.69 | 1900 | 5.5419 | |
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| 5.4266 | 0.73 | 2000 | 5.5428 | |
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| 5.4848 | 0.77 | 2100 | 5.5438 | |
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| 5.5069 | 0.8 | 2200 | 5.5446 | |
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| 5.5885 | 0.84 | 2300 | 5.5469 | |
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| 5.4484 | 0.88 | 2400 | 5.5462 | |
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| 5.3859 | 0.91 | 2500 | 5.5475 | |
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| 5.465 | 0.95 | 2600 | 5.5476 | |
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| 5.4355 | 0.99 | 2700 | 5.5477 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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