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# lmind_nq_train1000_eval500_v1_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_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2634
- Accuracy: 0.4175

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.545         | 1.0   | 63   | 2.3751          | 0.4277   |
| 1.7472        | 2.0   | 126  | 2.4026          | 0.4278   |
| 1.1646        | 3.0   | 189  | 2.5881          | 0.4251   |
| 0.7965        | 4.0   | 252  | 2.7525          | 0.4225   |
| 0.6475        | 5.0   | 315  | 2.8674          | 0.4237   |
| 0.5615        | 6.0   | 378  | 2.9355          | 0.4226   |
| 0.5155        | 7.0   | 441  | 3.0023          | 0.4181   |
| 0.5173        | 8.0   | 504  | 3.0241          | 0.4221   |
| 0.4722        | 9.0   | 567  | 3.1103          | 0.4139   |
| 0.4768        | 10.0  | 630  | 3.1335          | 0.4206   |
| 0.4573        | 11.0  | 693  | 3.1025          | 0.4213   |
| 0.4472        | 12.0  | 756  | 3.1968          | 0.4156   |
| 0.4395        | 13.0  | 819  | 3.1920          | 0.4183   |
| 0.4303        | 14.0  | 882  | 3.2299          | 0.4172   |
| 0.4146        | 15.0  | 945  | 3.2276          | 0.4155   |
| 0.4283        | 16.0  | 1008 | 3.2443          | 0.4203   |
| 0.4246        | 17.0  | 1071 | 3.2566          | 0.4172   |
| 0.4116        | 18.0  | 1134 | 3.2287          | 0.4206   |
| 0.4117        | 19.0  | 1197 | 3.2413          | 0.4188   |
| 0.4064        | 20.0  | 1260 | 3.2634          | 0.4175   |


### 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": "gpt2-xl", "model-index": [{"name": "lmind_nq_train1000_eval500_v1_qa_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": 0.4175483870967742, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train1000_eval500_v1_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us