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---
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train600_eval300_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train600_eval300_v1_recite_qa_gpt2-xl_1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train600_eval300_v1_recite_qa
type: tyzhu/lmind_nq_train600_eval300_v1_recite_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.8390196078431372
---
<!-- 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_train600_eval300_v1_recite_qa_gpt2-xl_1e-4
This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_nq_train600_eval300_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3982
- Accuracy: 0.8390
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0096 | 1.0 | 93 | 1.3802 | 0.6793 |
| 0.7666 | 2.0 | 186 | 0.6686 | 0.7849 |
| 0.31 | 3.0 | 279 | 0.4719 | 0.8184 |
| 0.1608 | 4.0 | 372 | 0.4038 | 0.8311 |
| 0.1101 | 5.0 | 465 | 0.3742 | 0.8372 |
| 0.0839 | 6.0 | 558 | 0.3734 | 0.8393 |
| 0.0743 | 7.0 | 651 | 0.3625 | 0.8404 |
| 0.0756 | 8.0 | 744 | 0.3654 | 0.8399 |
| 0.0694 | 9.0 | 837 | 0.3742 | 0.8400 |
| 0.0669 | 10.0 | 930 | 0.3712 | 0.8403 |
| 0.0692 | 11.0 | 1023 | 0.3812 | 0.8397 |
| 0.0717 | 12.0 | 1116 | 0.3797 | 0.8395 |
| 0.0762 | 13.0 | 1209 | 0.3892 | 0.8393 |
| 0.0823 | 14.0 | 1302 | 0.3993 | 0.8384 |
| 0.0789 | 15.0 | 1395 | 0.3946 | 0.8389 |
| 0.0737 | 16.0 | 1488 | 0.3927 | 0.8393 |
| 0.0739 | 17.0 | 1581 | 0.3977 | 0.8381 |
| 0.0741 | 18.0 | 1674 | 0.4060 | 0.8379 |
| 0.0741 | 19.0 | 1767 | 0.4047 | 0.8389 |
| 0.0715 | 20.0 | 1860 | 0.3982 | 0.8390 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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