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# lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_nq_train5000_eval5000_v1_docidx dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5208
- Accuracy: 0.8848

## 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 |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 2.4446        | 1.0   | 561   | 0.7075   | 2.1587          |
| 1.9645        | 2.0   | 1122  | 0.7463   | 1.7202          |
| 1.5108        | 3.0   | 1683  | 0.7894   | 1.2986          |
| 1.1362        | 4.0   | 2244  | 0.8263   | 0.9717          |
| 0.823         | 5.0   | 2805  | 0.8535   | 0.7567          |
| 0.5827        | 6.0   | 3366  | 0.8686   | 0.6158          |
| 0.4107        | 7.0   | 3927  | 0.8772   | 0.5425          |
| 0.2984        | 8.0   | 4488  | 0.8809   | 0.5119          |
| 0.2263        | 9.0   | 5049  | 0.8826   | 0.4956          |
| 0.1849        | 10.0  | 5610  | 0.8834   | 0.5079          |
| 0.1587        | 11.0  | 6171  | 0.8839   | 0.4955          |
| 0.1412        | 12.0  | 6732  | 0.8841   | 0.5088          |
| 0.1286        | 13.0  | 7293  | 0.8842   | 0.5055          |
| 0.1202        | 14.0  | 7854  | 0.8843   | 0.4976          |
| 0.1119        | 15.0  | 8415  | 0.8845   | 0.5087          |
| 0.1092        | 16.0  | 8976  | 0.8846   | 0.5038          |
| 0.1066        | 17.0  | 9537  | 0.8846   | 0.5024          |
| 0.1018        | 18.0  | 10098 | 0.8847   | 0.5413          |
| 0.1012        | 19.0  | 10659 | 0.8847   | 0.5270          |
| 0.0989        | 20.0  | 11220 | 0.8848   | 0.5208          |


### 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_train5000_eval5000_v1_docidx"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train5000_eval5000_v1_docidx", "type": "tyzhu/lmind_nq_train5000_eval5000_v1_docidx"}, "metrics": [{"type": "accuracy", "value": 0.8847917572397486, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train5000_eval5000_v1_docidx base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us