metadata
license: mit
base_model: gpt2-xl
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train300_eval100_v1_recite_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train300_eval100_v1_recite_qa_gpt2-xl
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train300_eval100_v1_recite_qa
type: tyzhu/lmind_nq_train300_eval100_v1_recite_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.8212156862745098
lmind_nq_train300_eval100_v1_recite_qa_gpt2-xl
This model is a fine-tuned version of gpt2-xl on the tyzhu/lmind_nq_train300_eval100_v1_recite_qa dataset. It achieves the following results on the evaluation set:
- Loss: 0.3388
- Accuracy: 0.8212
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: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1943 | 1.0 | 44 | 0.4267 | 0.8042 |
| 0.1121 | 2.0 | 88 | 0.3744 | 0.8138 |
| 0.0832 | 3.0 | 132 | 0.3551 | 0.8177 |
| 0.0859 | 4.0 | 176 | 0.3487 | 0.8187 |
| 0.0849 | 5.0 | 220 | 0.3478 | 0.8188 |
| 0.0791 | 6.0 | 264 | 0.3479 | 0.8194 |
| 0.0681 | 7.0 | 308 | 0.3537 | 0.8197 |
| 0.0715 | 8.0 | 352 | 0.3467 | 0.8205 |
| 0.0639 | 9.0 | 396 | 0.3577 | 0.8194 |
| 0.0614 | 10.0 | 440 | 0.3388 | 0.8212 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1