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# lmind_nq_train1000_eval500_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_train1000_eval500_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3712
- Accuracy: 0.8446

## 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1808        | 1.0   | 154  | 1.8207          | 0.6294   |
| 1.4349        | 2.0   | 308  | 1.2914          | 0.6957   |
| 0.8529        | 3.0   | 462  | 0.8566          | 0.7584   |
| 0.4829        | 4.0   | 616  | 0.5789          | 0.8049   |
| 0.2798        | 5.0   | 770  | 0.4421          | 0.8269   |
| 0.1904        | 6.0   | 924  | 0.3886          | 0.8373   |
| 0.1351        | 7.0   | 1078 | 0.3645          | 0.8411   |
| 0.1053        | 8.0   | 1232 | 0.3556          | 0.8431   |
| 0.0889        | 9.0   | 1386 | 0.3492          | 0.8432   |
| 0.0801        | 10.0  | 1540 | 0.3630          | 0.8441   |
| 0.0768        | 11.0  | 1694 | 0.3605          | 0.8445   |
| 0.0729        | 12.0  | 1848 | 0.3607          | 0.8444   |
| 0.0706        | 13.0  | 2002 | 0.3570          | 0.8450   |
| 0.07          | 14.0  | 2156 | 0.3634          | 0.8447   |
| 0.0697        | 15.0  | 2310 | 0.3627          | 0.8447   |
| 0.0681        | 16.0  | 2464 | 0.3645          | 0.8446   |
| 0.0685        | 17.0  | 2618 | 0.3652          | 0.8443   |
| 0.0683        | 18.0  | 2772 | 0.3646          | 0.8442   |
| 0.0665        | 19.0  | 2926 | 0.3732          | 0.8444   |
| 0.0659        | 20.0  | 3080 | 0.3712          | 0.8446   |


### 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_train1000_eval500_v1_recite_qa"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train1000_eval500_v1_recite_qa_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train1000_eval500_v1_recite_qa", "type": "tyzhu/lmind_nq_train1000_eval500_v1_recite_qa"}, "metrics": [{"type": "accuracy", "value": 0.8446196078431373, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train1000_eval500_v1_recite_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us