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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Fraser/short-jokes |
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metrics: |
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- accuracy |
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model-index: |
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- name: gpt2-jokes |
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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: Fraser/short-jokes |
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type: Fraser/short-jokes |
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config: default |
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split: train[:5%] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8795507387461411 |
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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-jokes |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the Fraser/short-jokes dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6748 |
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- Accuracy: 0.8796 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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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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| No log | 0.06 | 100 | 0.7285 | 0.8732 | |
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| No log | 0.12 | 200 | 0.7141 | 0.8747 | |
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| No log | 0.17 | 300 | 0.7056 | 0.8757 | |
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| No log | 0.23 | 400 | 0.6992 | 0.8764 | |
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| 0.7907 | 0.29 | 500 | 0.6942 | 0.8771 | |
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| 0.7907 | 0.35 | 600 | 0.6906 | 0.8777 | |
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| 0.7907 | 0.41 | 700 | 0.6873 | 0.8779 | |
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| 0.7907 | 0.47 | 800 | 0.6848 | 0.8782 | |
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| 0.7907 | 0.52 | 900 | 0.6830 | 0.8786 | |
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| 0.7105 | 0.58 | 1000 | 0.6809 | 0.8788 | |
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| 0.7105 | 0.64 | 1100 | 0.6794 | 0.8790 | |
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| 0.7105 | 0.7 | 1200 | 0.6780 | 0.8792 | |
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| 0.7105 | 0.76 | 1300 | 0.6770 | 0.8793 | |
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| 0.7105 | 0.81 | 1400 | 0.6760 | 0.8794 | |
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| 0.7034 | 0.87 | 1500 | 0.6755 | 0.8794 | |
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| 0.7034 | 0.93 | 1600 | 0.6750 | 0.8795 | |
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| 0.7034 | 0.99 | 1700 | 0.6748 | 0.8795 | |
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### Framework versions |
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- Transformers 4.28.0.dev0 |
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- Pytorch 2.0.0-rc1 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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