---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_recite_qa_gpt2-xl
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa
      type: tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7664424114149346
---

<!-- 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_train8000_eval7405_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_train8000_eval7405_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4650
- Accuracy: 0.7664

## 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  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.9537        | 1.0   | 2179  | 0.6693   | 1.5623          |
| 1.4734        | 2.0   | 4358  | 0.6924   | 1.2099          |
| 1.0665        | 3.0   | 6537  | 0.7147   | 0.9178          |
| 0.7684        | 4.0   | 8716  | 0.7331   | 0.6988          |
| 0.548         | 5.0   | 10895 | 0.7466   | 0.5567          |
| 0.4039        | 6.0   | 13074 | 0.7551   | 0.4728          |
| 0.3044        | 7.0   | 15253 | 0.7600   | 0.4376          |
| 0.2446        | 8.0   | 17432 | 0.7628   | 0.4220          |
| 0.2039        | 9.0   | 19611 | 0.7642   | 0.4190          |
| 0.1787        | 10.0  | 21790 | 0.7649   | 0.4250          |
| 0.1652        | 11.0  | 23969 | 0.7654   | 0.4295          |
| 0.154         | 12.0  | 26148 | 0.7655   | 0.4366          |
| 0.1441        | 13.0  | 28327 | 0.7657   | 0.4429          |
| 0.143         | 14.0  | 30506 | 0.7657   | 0.4418          |
| 0.1366        | 15.0  | 32685 | 0.7661   | 0.4469          |
| 0.1335        | 16.0  | 34864 | 0.7661   | 0.4517          |
| 0.1299        | 17.0  | 37043 | 0.7662   | 0.4534          |
| 0.1271        | 18.0  | 39222 | 0.7664   | 0.4579          |
| 0.1268        | 19.0  | 41401 | 0.7664   | 0.4556          |
| 0.1238        | 20.0  | 43580 | 0.4650   | 0.7664          |


### Framework versions

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