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# lmind_nq_train5000_eval5000_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_train5000_eval5000_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3682
- Accuracy: 0.8792

## 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 |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 2.1509        | 1.0   | 873   | 0.7132   | 1.7318          |
| 1.4733        | 2.0   | 1746  | 0.7619   | 1.2526          |
| 0.956         | 3.0   | 2619  | 0.8076   | 0.8630          |
| 0.6185        | 4.0   | 3492  | 0.8424   | 0.5905          |
| 0.4012        | 5.0   | 4365  | 0.8635   | 0.4375          |
| 0.2724        | 6.0   | 5238  | 0.8726   | 0.3726          |
| 0.1944        | 7.0   | 6111  | 0.8762   | 0.3524          |
| 0.1556        | 8.0   | 6984  | 0.8777   | 0.3441          |
| 0.1291        | 9.0   | 7857  | 0.8783   | 0.3419          |
| 0.1158        | 10.0  | 8730  | 0.8786   | 0.3441          |
| 0.1085        | 11.0  | 9603  | 0.8789   | 0.3491          |
| 0.1023        | 12.0  | 10476 | 0.8790   | 0.3513          |
| 0.0999        | 13.0  | 11349 | 0.8789   | 0.3513          |
| 0.0972        | 14.0  | 12222 | 0.8792   | 0.3525          |
| 0.0935        | 15.0  | 13095 | 0.8791   | 0.3588          |
| 0.0917        | 16.0  | 13968 | 0.8787   | 0.3614          |
| 0.0894        | 17.0  | 14841 | 0.8793   | 0.3578          |
| 0.0882        | 18.0  | 15714 | 0.8794   | 0.3630          |
| 0.0849        | 19.0  | 16587 | 0.8793   | 0.3639          |
| 0.0845        | 20.0  | 17460 | 0.8792   | 0.3682          |


### 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_recite_qa"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train5000_eval5000_v1_recite_qa_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train5000_eval5000_v1_recite_qa", "type": "tyzhu/lmind_nq_train5000_eval5000_v1_recite_qa"}, "metrics": [{"type": "accuracy", "value": 0.8792413793103449, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train5000_eval5000_v1_recite_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us