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# lmind_nq_train1000_eval500_v1_qa_tyzhu_lmind_nq_train1000_eval500_v1_docidx_gpt2-xl

This model is a fine-tuned version of [tyzhu/lmind_nq_train1000_eval500_v1_docidx_gpt2-xl](https://huggingface.co/tyzhu/lmind_nq_train1000_eval500_v1_docidx_gpt2-xl) on the tyzhu/lmind_nq_train1000_eval500_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0583
- Accuracy: 0.4375

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.3754        | 1.0   | 63   | 2.2151          | 0.4425   |
| 1.5792        | 2.0   | 126  | 2.2979          | 0.4422   |
| 1.0502        | 3.0   | 189  | 2.4279          | 0.4415   |
| 0.7036        | 4.0   | 252  | 2.5927          | 0.4372   |
| 0.6131        | 5.0   | 315  | 2.6762          | 0.4381   |
| 0.5451        | 6.0   | 378  | 2.7837          | 0.4325   |
| 0.5122        | 7.0   | 441  | 2.8127          | 0.4326   |
| 0.4894        | 8.0   | 504  | 2.8456          | 0.4358   |
| 0.4682        | 9.0   | 567  | 2.8674          | 0.4255   |
| 0.471         | 10.0  | 630  | 2.9373          | 0.4321   |
| 0.4507        | 11.0  | 693  | 2.9652          | 0.4255   |
| 0.4406        | 12.0  | 756  | 2.9742          | 0.4298   |
| 0.4388        | 13.0  | 819  | 3.0183          | 0.4313   |
| 0.4223        | 14.0  | 882  | 3.0322          | 0.4308   |
| 0.4232        | 15.0  | 945  | 3.0413          | 0.4292   |
| 0.4284        | 16.0  | 1008 | 3.0487          | 0.4330   |
| 0.4258        | 17.0  | 1071 | 3.0773          | 0.4301   |
| 0.4212        | 18.0  | 1134 | 3.0315          | 0.4357   |
| 0.4156        | 19.0  | 1197 | 2.9772          | 0.4397   |
| 0.4132        | 20.0  | 1260 | 3.0583          | 0.4375   |


### 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_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_nq_train1000_eval500_v1_docidx_gpt2-xl", "model-index": [{"name": "lmind_nq_train1000_eval500_v1_qa_tyzhu_lmind_nq_train1000_eval500_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train1000_eval500_v1_qa", "type": "tyzhu/lmind_nq_train1000_eval500_v1_qa"}, "metrics": [{"type": "accuracy", "value": 0.4375483870967742, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train1000_eval500_v1_qa base_model:tyzhu/lmind_nq_train1000_eval500_v1_docidx_gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us