---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train1000_eval200_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train1000_eval200_v1_recite_qa_gpt2-xl
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train1000_eval200_v1_recite_qa
      type: tyzhu/lmind_hotpot_train1000_eval200_v1_recite_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6988971684053651
---

<!-- 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_eval200_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_eval200_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4436
- Accuracy: 0.6989

## 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: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7644        | 1.0   | 211  | 1.0036          | 0.6429   |
| 0.526         | 2.0   | 422  | 0.7351          | 0.6658   |
| 0.4163        | 3.0   | 633  | 0.5744          | 0.6815   |
| 0.2864        | 4.0   | 844  | 0.4953          | 0.6899   |
| 0.2118        | 5.0   | 1055 | 0.4594          | 0.6944   |
| 0.17          | 6.0   | 1266 | 0.4490          | 0.6964   |
| 0.134         | 7.0   | 1477 | 0.4369          | 0.6979   |
| 0.1206        | 8.0   | 1688 | 0.4372          | 0.6987   |
| 0.1081        | 9.0   | 1899 | 0.4423          | 0.6987   |
| 0.1053        | 10.0  | 2110 | 0.4436          | 0.6989   |


### Framework versions

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