clm
This model is a fine-tuned version of distilgpt2 on the wikitext wikitext-2-raw-v1 dataset. It achieves the following results on the evaluation set:
- Loss: 3.4802
- Accuracy: 0.3719
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: 8
- eval_batch_size: 8
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.6158 | 0.99 | 72 | 3.4802 | 0.3719 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for nomsgadded/clm
Base model
distilbert/distilgpt2Dataset used to train nomsgadded/clm
Evaluation results
- Accuracy on wikitext wikitext-2-raw-v1validation set self-reported0.372