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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gpt2-p10k |
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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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# gpt2-p10k |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0241 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| No log | 0.2 | 200 | 0.0558 | |
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| No log | 0.4 | 400 | 0.1944 | |
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| 0.2826 | 0.6 | 600 | 0.3970 | |
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| 0.2826 | 0.8 | 800 | 0.6245 | |
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| 0.8928 | 1.0 | 1000 | 2.0545 | |
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| 0.8928 | 1.2 | 1200 | 0.3789 | |
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| 0.8928 | 1.4 | 1400 | 0.4120 | |
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| 0.5735 | 1.6 | 1600 | 0.9738 | |
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| 0.5735 | 1.8 | 1800 | 1.4284 | |
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| 3.2584 | 2.0 | 2000 | 3.8628 | |
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| 3.2584 | 2.2 | 2200 | 0.6803 | |
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| 3.2584 | 2.4 | 2400 | 0.4168 | |
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| 1.1454 | 2.6 | 2600 | 0.0628 | |
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| 1.1454 | 2.8 | 2800 | 0.0353 | |
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| 0.0693 | 3.0 | 3000 | 0.0301 | |
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| 0.0693 | 3.2 | 3200 | 0.0294 | |
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| 0.0693 | 3.4 | 3400 | 0.0284 | |
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| 0.0299 | 3.6 | 3600 | 0.0279 | |
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| 0.0299 | 3.8 | 3800 | 0.0274 | |
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| 0.0287 | 4.0 | 4000 | 0.0274 | |
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| 0.0287 | 4.2 | 4200 | 0.0271 | |
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| 0.0287 | 4.4 | 4400 | 0.0260 | |
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| 0.0274 | 4.6 | 4600 | 0.0260 | |
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| 0.0274 | 4.8 | 4800 | 0.0261 | |
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| 0.0267 | 5.0 | 5000 | 0.0257 | |
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| 0.0267 | 5.2 | 5200 | 0.0255 | |
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| 0.0267 | 5.4 | 5400 | 0.0255 | |
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| 0.0263 | 5.6 | 5600 | 0.0254 | |
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| 0.0263 | 5.8 | 5800 | 0.0250 | |
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| 0.0259 | 6.0 | 6000 | 0.0250 | |
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| 0.0259 | 6.2 | 6200 | 0.0252 | |
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| 0.0259 | 6.4 | 6400 | 0.0253 | |
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| 0.0256 | 6.6 | 6600 | 0.0250 | |
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| 0.0256 | 6.8 | 6800 | 0.0247 | |
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| 0.0253 | 7.0 | 7000 | 0.0256 | |
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| 0.0253 | 7.2 | 7200 | 0.0247 | |
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| 0.0253 | 7.4 | 7400 | 0.0245 | |
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| 0.0251 | 7.6 | 7600 | 0.0245 | |
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| 0.0251 | 7.8 | 7800 | 0.0245 | |
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| 0.0251 | 8.0 | 8000 | 0.0246 | |
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| 0.0251 | 8.2 | 8200 | 0.0244 | |
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| 0.0251 | 8.4 | 8400 | 0.0246 | |
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| 0.0252 | 8.6 | 8600 | 0.0243 | |
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| 0.0252 | 8.8 | 8800 | 0.0242 | |
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| 0.0244 | 9.0 | 9000 | 0.0242 | |
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| 0.0244 | 9.2 | 9200 | 0.0242 | |
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| 0.0244 | 9.4 | 9400 | 0.0242 | |
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| 0.0247 | 9.6 | 9600 | 0.0242 | |
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| 0.0247 | 9.8 | 9800 | 0.0241 | |
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| 0.0245 | 10.0 | 10000 | 0.0241 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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