DistilGPT2-model
This model is a fine-tuned version of distilbert/distilgpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2126
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 250
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.7168 | 0.0 | 25 | 2.6101 |
2.652 | 0.0 | 50 | 2.5280 |
2.5867 | 0.0 | 75 | 2.4430 |
2.5081 | 0.0 | 100 | 2.3748 |
2.4728 | 0.0 | 125 | 2.3105 |
2.4563 | 0.0 | 150 | 2.2719 |
2.3669 | 0.01 | 175 | 2.2473 |
2.3839 | 0.01 | 200 | 2.2292 |
2.3617 | 0.01 | 225 | 2.2150 |
2.3729 | 0.01 | 250 | 2.2126 |
Framework versions
- PEFT 0.8.2
- Transformers 4.38.1
- Pytorch 1.13.1
- Datasets 2.17.0
- Tokenizers 0.15.2
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Model tree for anushkat/DistilGPT2-model
Base model
distilbert/distilgpt2