---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
      type: tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7496011644832605
---

<!-- 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_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4181
- Accuracy: 0.7496

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9823        | 1.0   | 248  | 1.6149          | 0.6398   |
| 1.3868        | 2.0   | 496  | 1.1929          | 0.6700   |
| 0.9102        | 3.0   | 744  | 0.8513          | 0.6992   |
| 0.5869        | 4.0   | 992  | 0.6181          | 0.7218   |
| 0.364         | 5.0   | 1240 | 0.4963          | 0.7352   |
| 0.2706        | 6.0   | 1488 | 0.4413          | 0.7420   |
| 0.1906        | 7.0   | 1736 | 0.4085          | 0.7458   |
| 0.1474        | 8.0   | 1984 | 0.4010          | 0.7477   |
| 0.1264        | 9.0   | 2232 | 0.3979          | 0.7484   |
| 0.1091        | 10.0  | 2480 | 0.4060          | 0.7487   |
| 0.1072        | 11.0  | 2728 | 0.4050          | 0.7490   |
| 0.0969        | 12.0  | 2976 | 0.4081          | 0.7492   |
| 0.0935        | 13.0  | 3224 | 0.4145          | 0.7495   |
| 0.0932        | 14.0  | 3472 | 0.4078          | 0.7494   |
| 0.0929        | 15.0  | 3720 | 0.4140          | 0.7494   |
| 0.0951        | 16.0  | 3968 | 0.4145          | 0.7495   |
| 0.0926        | 17.0  | 4216 | 0.4134          | 0.7495   |
| 0.0946        | 18.0  | 4464 | 0.4257          | 0.7493   |
| 0.0897        | 19.0  | 4712 | 0.4164          | 0.7496   |
| 0.092         | 20.0  | 4960 | 0.4181          | 0.7496   |


### Framework versions

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