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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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metrics: |
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- accuracy |
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library_name: peft |
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model-index: |
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- name: p-tuning-t2t-gpt2-large-with-sst2 |
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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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# p-tuning-t2t-gpt2-large-with-sst2 |
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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: 0.4929 |
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- Accuracy: 0.7741 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- num_epochs: 20 |
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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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| 0.6984 | 1.0 | 4210 | 0.7020 | 0.5138 | |
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| 0.6766 | 2.0 | 8420 | 0.6971 | 0.5138 | |
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| 0.5377 | 3.0 | 12630 | 0.5625 | 0.7087 | |
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| 0.5375 | 4.0 | 16840 | 0.5481 | 0.7282 | |
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| 0.5209 | 5.0 | 21050 | 0.5278 | 0.7420 | |
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| 0.5235 | 6.0 | 25260 | 0.5357 | 0.7374 | |
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| 0.5311 | 7.0 | 29470 | 0.5342 | 0.7294 | |
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| 0.5545 | 8.0 | 33680 | 0.5135 | 0.7511 | |
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| 0.5406 | 9.0 | 37890 | 0.5138 | 0.7397 | |
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| 0.523 | 10.0 | 42100 | 0.5192 | 0.7580 | |
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| 0.5248 | 11.0 | 46310 | 0.4997 | 0.7706 | |
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| 0.559 | 12.0 | 50520 | 0.5063 | 0.7649 | |
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| 0.582 | 13.0 | 54730 | 0.4958 | 0.7741 | |
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| 0.4796 | 14.0 | 58940 | 0.4981 | 0.7706 | |
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| 0.4173 | 15.0 | 63150 | 0.4911 | 0.7626 | |
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| 0.4449 | 16.0 | 67360 | 0.4932 | 0.7718 | |
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| 0.4697 | 17.0 | 71570 | 0.4917 | 0.7741 | |
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| 0.3779 | 18.0 | 75780 | 0.4931 | 0.7729 | |
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| 0.449 | 19.0 | 79990 | 0.4929 | 0.7729 | |
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| 0.4938 | 20.0 | 84200 | 0.4929 | 0.7741 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.1 |
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- Pytorch 2.5.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
