---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train300_eval100_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train300_eval100_v1_recite_qa_gpt2-xl
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_nq_train300_eval100_v1_recite_qa
      type: tyzhu/lmind_nq_train300_eval100_v1_recite_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8212156862745098
---

<!-- 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_train300_eval100_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_train300_eval100_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3388
- Accuracy: 0.8212

## 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: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1943        | 1.0   | 44   | 0.4267          | 0.8042   |
| 0.1121        | 2.0   | 88   | 0.3744          | 0.8138   |
| 0.0832        | 3.0   | 132  | 0.3551          | 0.8177   |
| 0.0859        | 4.0   | 176  | 0.3487          | 0.8187   |
| 0.0849        | 5.0   | 220  | 0.3478          | 0.8188   |
| 0.0791        | 6.0   | 264  | 0.3479          | 0.8194   |
| 0.0681        | 7.0   | 308  | 0.3537          | 0.8197   |
| 0.0715        | 8.0   | 352  | 0.3467          | 0.8205   |
| 0.0639        | 9.0   | 396  | 0.3577          | 0.8194   |
| 0.0614        | 10.0  | 440  | 0.3388          | 0.8212   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1