---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train5000_eval5000_v1_recite_qa_gpt2-xl
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa
      type: tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7660672947510094
---

<!-- 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_train5000_eval5000_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_train5000_eval5000_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4522
- Accuracy: 0.7661

## 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 |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.9686        | 1.0   | 1452  | 0.6681   | 1.5662          |
| 1.4604        | 2.0   | 2904  | 0.6915   | 1.2069          |
| 1.0522        | 3.0   | 4356  | 0.7149   | 0.9046          |
| 0.7455        | 4.0   | 5808  | 0.7341   | 0.6844          |
| 0.5307        | 5.0   | 7260  | 0.7475   | 0.5420          |
| 0.3796        | 6.0   | 8712  | 0.7560   | 0.4609          |
| 0.2912        | 7.0   | 10164 | 0.7604   | 0.4311          |
| 0.2282        | 8.0   | 11616 | 0.7627   | 0.4184          |
| 0.1905        | 9.0   | 13068 | 0.7640   | 0.4136          |
| 0.1687        | 10.0  | 14520 | 0.7648   | 0.4175          |
| 0.1553        | 11.0  | 15972 | 0.7651   | 0.4212          |
| 0.1447        | 12.0  | 17424 | 0.7653   | 0.4283          |
| 0.1388        | 13.0  | 18876 | 0.7656   | 0.4287          |
| 0.1329        | 14.0  | 20328 | 0.7657   | 0.4349          |
| 0.1292        | 15.0  | 21780 | 0.7657   | 0.4353          |
| 0.1267        | 16.0  | 23232 | 0.7659   | 0.4383          |
| 0.1251        | 17.0  | 24684 | 0.4416   | 0.7661          |
| 0.1201        | 18.0  | 26136 | 0.4467   | 0.7659          |
| 0.1186        | 19.0  | 27588 | 0.4508   | 0.7660          |
| 0.1176        | 20.0  | 29040 | 0.4522   | 0.7661          |


### Framework versions

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