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# lmind_nq_full_v1_recite_qa_gpt2-large

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1238
- Accuracy: 0.6818

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 2.3143        | 1.0   | 3205  | 0.6905   | 2.0189          |
| 2.2229        | 2.0   | 6410  | 0.6946   | 1.9813          |
| 4.9465        | 3.0   | 9615  | 2.1218   | 0.6820          |
| 2.6192        | 4.0   | 12820 | 2.1720   | 0.6774          |
| 2.6012        | 5.0   | 16025 | 2.2369   | 0.6706          |
| 2.329         | 6.0   | 19230 | 2.0791   | 0.6854          |
| 2.9852        | 7.0   | 22435 | 2.3881   | 0.6603          |
| 5.1178        | 8.0   | 25640 | 2.5784   | 0.6442          |
| 2.5182        | 9.0   | 28845 | 2.1481   | 0.6798          |
| 2.4994        | 10.0  | 32050 | 2.1238   | 0.6818          |


### 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"], "metrics": ["accuracy"], "base_model": "gpt2-large", "model-index": [{"name": "lmind_nq_full_v1_recite_qa_gpt2-large", "results": []}]}
transformers pytorch gpt2 text-generation generated_from_trainer base_model:gpt2-large license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us