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# lmind_nq_train600_eval300_v1_recite_qa_gpt2-xl

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_nq_train600_eval300_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3660
- Accuracy: 0.8407

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.4392        | 0.51  | 47   | 0.5938   | 2.1629          |
| 2.2015        | 1.01  | 94   | 0.6250   | 1.8377          |
| 1.5193        | 1.52  | 141  | 0.6524   | 1.8218          |
| 1.405         | 2.02  | 188  | 0.6983   | 1.2418          |
| 0.8654        | 2.53  | 235  | 0.7264   | 1.0606          |
| 0.7158        | 3.03  | 282  | 0.7665   | 0.7902          |
| 0.4185        | 3.54  | 329  | 0.7867   | 0.6745          |
| 0.4556        | 4.04  | 376  | 0.8105   | 0.5201          |
| 0.253         | 4.55  | 423  | 0.8198   | 0.4699          |
| 0.1895        | 5.05  | 470  | 0.8301   | 0.4096          |
| 0.1649        | 5.56  | 517  | 0.8323   | 0.3918          |
| 0.1468        | 6.06  | 564  | 0.8367   | 0.3684          |
| 0.1179        | 6.57  | 611  | 0.8377   | 0.3645          |
| 0.1171        | 7.08  | 658  | 0.8394   | 0.3590          |
| 0.0953        | 7.58  | 705  | 0.8402   | 0.3537          |
| 0.0831        | 8.09  | 752  | 0.8400   | 0.3615          |
| 0.0824        | 8.59  | 799  | 0.8408   | 0.3527          |
| 0.0764        | 9.1   | 846  | 0.8410   | 0.3586          |
| 0.0731        | 9.6   | 893  | 0.8408   | 0.3589          |
| 0.0637        | 10.11 | 940  | 0.3618   | 0.8412          |
| 0.069         | 10.61 | 987  | 0.3563   | 0.8415          |
| 0.0636        | 11.12 | 1034 | 0.3650   | 0.8409          |
| 0.0663        | 11.62 | 1081 | 0.3554   | 0.8418          |
| 0.0636        | 12.13 | 1128 | 0.3675   | 0.8409          |
| 0.0632        | 12.63 | 1175 | 0.3590   | 0.8418          |
| 0.0605        | 13.14 | 1222 | 0.3635   | 0.8413          |
| 0.0621        | 13.65 | 1269 | 0.3558   | 0.8413          |
| 0.0579        | 14.15 | 1316 | 0.3682   | 0.8410          |
| 0.0618        | 14.66 | 1363 | 0.3653   | 0.8405          |
| 0.0552        | 15.16 | 1410 | 0.3661   | 0.8413          |
| 0.0619        | 15.67 | 1457 | 0.3596   | 0.8416          |
| 0.0536        | 16.17 | 1504 | 0.3710   | 0.8414          |
| 0.0602        | 16.68 | 1551 | 0.3609   | 0.8418          |
| 0.054         | 17.18 | 1598 | 0.3759   | 0.8410          |
| 0.0635        | 17.69 | 1645 | 0.3597   | 0.8414          |
| 0.0536        | 18.19 | 1692 | 0.3750   | 0.8410          |
| 0.0588        | 18.7  | 1739 | 0.3684   | 0.8414          |
| 0.0713        | 19.2  | 1786 | 0.3691   | 0.8411          |
| 0.0704        | 19.71 | 1833 | 0.3638   | 0.8413          |


### 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/lmind_nq_train600_eval300_v1_recite_qa"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train600_eval300_v1_recite_qa_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train600_eval300_v1_recite_qa", "type": "tyzhu/lmind_nq_train600_eval300_v1_recite_qa"}, "metrics": [{"type": "accuracy", "value": 0.8407058823529412, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train600_eval300_v1_recite_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us