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# squad_qa_wrong_num_v5_full_recite_full_passage_gpt2-large

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the tyzhu/squad_qa_wrong_num_v5_full_recite_full_passage dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5586
- Accuracy: 0.8677

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 100.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.5561        | 1.0   | 317   | 0.8281   | 0.7064          |
| 0.2967        | 2.0   | 634   | 0.8686   | 0.3410          |
| 0.1795        | 3.0   | 951   | 0.8695   | 0.3332          |
| 0.1476        | 4.0   | 1268  | 0.8706   | 0.3420          |
| 0.128         | 5.0   | 1585  | 0.8682   | 0.3556          |
| 0.1138        | 6.0   | 1902  | 0.8686   | 0.3631          |
| 0.1056        | 7.0   | 2219  | 0.8682   | 0.3731          |
| 0.0998        | 8.0   | 2536  | 0.8681   | 0.3794          |
| 0.0965        | 9.0   | 2853  | 0.8681   | 0.3893          |
| 0.0921        | 10.0  | 3170  | 0.8689   | 0.3841          |
| 0.0881        | 11.0  | 3487  | 0.8680   | 0.4052          |
| 0.0841        | 12.0  | 3804  | 0.8695   | 0.3963          |
| 0.0802        | 13.0  | 4121  | 0.8677   | 0.4135          |
| 0.0769        | 14.0  | 4438  | 0.8686   | 0.4060          |
| 0.0728        | 15.0  | 4755  | 0.8680   | 0.4101          |
| 0.069         | 16.0  | 5072  | 0.8682   | 0.4131          |
| 0.0667        | 17.0  | 5389  | 0.8677   | 0.4228          |
| 0.0651        | 18.0  | 5706  | 0.8682   | 0.4160          |
| 0.0642        | 19.0  | 6023  | 0.8682   | 0.4148          |
| 0.0639        | 20.0  | 6340  | 0.8685   | 0.4249          |
| 0.0632        | 21.0  | 6657  | 0.8681   | 0.4232          |
| 0.0625        | 22.0  | 6974  | 0.8685   | 0.4265          |
| 0.0608        | 23.0  | 7291  | 0.8682   | 0.4257          |
| 0.0602        | 24.0  | 7608  | 0.8679   | 0.4357          |
| 0.0587        | 25.0  | 7925  | 0.8681   | 0.4367          |
| 0.0592        | 26.0  | 8242  | 0.8684   | 0.4410          |
| 0.0596        | 27.0  | 8559  | 0.8681   | 0.4398          |
| 0.0581        | 28.0  | 8876  | 0.8680   | 0.4465          |
| 0.0592        | 29.0  | 9193  | 0.8680   | 0.4478          |
| 0.0583        | 30.0  | 9510  | 0.8683   | 0.4417          |
| 0.0575        | 31.0  | 9827  | 0.8684   | 0.4533          |
| 0.0574        | 32.0  | 10144 | 0.8682   | 0.4480          |
| 0.0575        | 33.0  | 10461 | 0.8681   | 0.4562          |
| 0.0566        | 34.0  | 10778 | 0.8686   | 0.4549          |
| 0.0559        | 35.0  | 11095 | 0.8682   | 0.4641          |
| 0.0558        | 36.0  | 11412 | 0.8684   | 0.4699          |
| 0.0558        | 37.0  | 11729 | 0.8687   | 0.4595          |
| 0.0566        | 38.0  | 12046 | 0.8682   | 0.4650          |
| 0.0559        | 39.0  | 12363 | 0.8682   | 0.4712          |
| 0.0553        | 40.0  | 12680 | 0.8682   | 0.4602          |
| 0.0551        | 41.0  | 12997 | 0.8681   | 0.4685          |
| 0.0547        | 42.0  | 13314 | 0.8684   | 0.4731          |
| 0.0539        | 43.0  | 13631 | 0.8687   | 0.4808          |
| 0.0539        | 44.0  | 13948 | 0.8684   | 0.4705          |
| 0.0535        | 45.0  | 14265 | 0.8682   | 0.4833          |
| 0.0521        | 46.0  | 14582 | 0.8683   | 0.4736          |
| 0.0514        | 47.0  | 14899 | 0.8680   | 0.4726          |
| 0.0502        | 48.0  | 15216 | 0.8682   | 0.4736          |
| 0.0492        | 49.0  | 15533 | 0.8681   | 0.4814          |
| 0.0495        | 50.0  | 15850 | 0.8681   | 0.4911          |
| 0.0488        | 51.0  | 16167 | 0.8683   | 0.4847          |
| 0.0475        | 52.0  | 16484 | 0.8683   | 0.4892          |
| 0.0473        | 53.0  | 16801 | 0.8680   | 0.4853          |
| 0.0473        | 54.0  | 17118 | 0.8682   | 0.4964          |
| 0.0461        | 55.0  | 17435 | 0.8681   | 0.4854          |
| 0.0456        | 56.0  | 17752 | 0.8681   | 0.5001          |
| 0.0459        | 57.0  | 18069 | 0.8684   | 0.4984          |
| 0.0451        | 58.0  | 18386 | 0.8678   | 0.5053          |
| 0.0461        | 59.0  | 18703 | 0.8678   | 0.5038          |
| 0.0446        | 60.0  | 19020 | 0.8680   | 0.4968          |
| 0.0438        | 61.0  | 19337 | 0.8681   | 0.5160          |
| 0.0442        | 62.0  | 19654 | 0.8679   | 0.5087          |
| 0.044         | 63.0  | 19971 | 0.8679   | 0.5142          |
| 0.0439        | 64.0  | 20288 | 0.8679   | 0.4958          |
| 0.0437        | 65.0  | 20605 | 0.8678   | 0.4987          |
| 0.0433        | 66.0  | 20922 | 0.8680   | 0.5183          |
| 0.0434        | 67.0  | 21239 | 0.8678   | 0.5145          |
| 0.0435        | 68.0  | 21556 | 0.8679   | 0.5226          |
| 0.0429        | 69.0  | 21873 | 0.8680   | 0.5340          |
| 0.0426        | 70.0  | 22190 | 0.8681   | 0.5534          |
| 0.0421        | 71.0  | 22507 | 0.8680   | 0.5435          |
| 0.0421        | 72.0  | 22824 | 0.8680   | 0.5418          |
| 0.0424        | 73.0  | 23141 | 0.8676   | 0.5475          |
| 0.0423        | 74.0  | 23458 | 0.8678   | 0.5214          |
| 0.0416        | 75.0  | 23775 | 0.8679   | 0.5353          |
| 0.0415        | 76.0  | 24092 | 0.8676   | 0.5441          |
| 0.042         | 77.0  | 24409 | 0.8677   | 0.5318          |
| 0.0418        | 78.0  | 24726 | 0.8678   | 0.5508          |
| 0.0406        | 79.0  | 25043 | 0.8678   | 0.5671          |
| 0.0407        | 80.0  | 25360 | 0.8679   | 0.5478          |
| 0.041         | 81.0  | 25677 | 0.8678   | 0.5318          |
| 0.0416        | 82.0  | 25994 | 0.8675   | 0.5418          |
| 0.0407        | 83.0  | 26311 | 0.8678   | 0.5485          |
| 0.0418        | 84.0  | 26628 | 0.8675   | 0.5461          |
| 0.0408        | 85.0  | 26945 | 0.8679   | 0.5538          |
| 0.041         | 86.0  | 27262 | 0.8677   | 0.5470          |
| 0.0407        | 87.0  | 27579 | 0.8679   | 0.5704          |
| 0.0404        | 88.0  | 27896 | 0.8676   | 0.5664          |
| 0.0403        | 89.0  | 28213 | 0.8676   | 0.5710          |
| 0.0401        | 90.0  | 28530 | 0.8676   | 0.5584          |
| 0.0409        | 91.0  | 28847 | 0.8677   | 0.5610          |
| 0.0405        | 92.0  | 29164 | 0.8677   | 0.5604          |
| 0.0407        | 93.0  | 29481 | 0.8676   | 0.5577          |
| 0.041         | 94.0  | 29798 | 0.8675   | 0.5566          |
| 0.0402        | 95.0  | 30115 | 0.8674   | 0.5663          |
| 0.0397        | 96.0  | 30432 | 0.8676   | 0.5547          |
| 0.0405        | 97.0  | 30749 | 0.8673   | 0.5606          |
| 0.0402        | 98.0  | 31066 | 0.5621   | 0.8676          |
| 0.0393        | 99.0  | 31383 | 0.5629   | 0.8674          |
| 0.0396        | 100.0 | 31700 | 0.5586   | 0.8677          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/squad_qa_wrong_num_v5_full_recite_full_passage"], "metrics": ["accuracy"], "base_model": "gpt2-large", "model-index": [{"name": "squad_qa_wrong_num_v5_full_recite_full_passage_gpt2-large", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/squad_qa_wrong_num_v5_full_recite_full_passage", "type": "tyzhu/squad_qa_wrong_num_v5_full_recite_full_passage"}, "metrics": [{"type": "accuracy", "value": 0.8677416860015468, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/squad_qa_wrong_num_v5_full_recite_full_passage base_model:gpt2-large license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us