codeparrot-ds
This model is a fine-tuned version of distilgpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9628
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.8291 | 0.09 | 500 | 3.1048 |
2.7568 | 0.19 | 1000 | 2.6598 |
2.4536 | 0.28 | 1500 | 2.4579 |
2.284 | 0.38 | 2000 | 2.3267 |
2.1605 | 0.47 | 2500 | 2.2221 |
2.0615 | 0.56 | 3000 | 2.1385 |
1.9799 | 0.66 | 3500 | 2.0642 |
1.9192 | 0.75 | 4000 | 2.0100 |
1.8725 | 0.84 | 4500 | 1.9766 |
1.8484 | 0.94 | 5000 | 1.9628 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for srsawant34/codeparrot-ds
Base model
distilbert/distilgpt2