|
|
--- |
|
|
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 |
|
|
|
