
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lmind_nq_train600_eval300_v1_qa_gpt2-xl_1e-4

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_nq_train600_eval300_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8511
- Accuracy: 0.3997

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.8634        | 1.0   | 38   | 2.5892          | 0.4186   |
| 1.5681        | 2.0   | 76   | 2.7748          | 0.4211   |
| 0.8548        | 3.0   | 114  | 3.1563          | 0.4135   |
| 0.7089        | 4.0   | 152  | 3.3480          | 0.4110   |
| 0.5823        | 5.0   | 190  | 3.5214          | 0.4065   |
| 0.5           | 6.0   | 228  | 3.5646          | 0.4086   |
| 0.5237        | 7.0   | 266  | 3.6945          | 0.4086   |
| 0.5075        | 8.0   | 304  | 3.7134          | 0.4072   |
| 0.4858        | 9.0   | 342  | 3.7086          | 0.4041   |
| 0.4467        | 10.0  | 380  | 3.7795          | 0.3968   |
| 0.4622        | 11.0  | 418  | 3.7785          | 0.4027   |
| 0.4584        | 12.0  | 456  | 3.9251          | 0.3942   |
| 0.451         | 13.0  | 494  | 3.7735          | 0.4068   |
| 0.4575        | 14.0  | 532  | 3.8526          | 0.4001   |
| 0.4261        | 15.0  | 570  | 3.8961          | 0.4031   |
| 0.4392        | 16.0  | 608  | 3.9279          | 0.3962   |
| 0.4483        | 17.0  | 646  | 3.9305          | 0.3990   |
| 0.4346        | 18.0  | 684  | 3.7755          | 0.3984   |
| 0.4364        | 19.0  | 722  | 3.9032          | 0.3995   |
| 0.424         | 20.0  | 760  | 3.8511          | 0.3997   |


### 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_qa"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train600_eval300_v1_qa_gpt2-xl_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train600_eval300_v1_qa", "type": "tyzhu/lmind_nq_train600_eval300_v1_qa"}, "metrics": [{"type": "accuracy", "value": 0.3996774193548387, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train600_eval300_v1_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us