codeparrot-ds-500sample-gpt-neo-2ep
This model is a fine-tuned version of EleutherAI/gpt-neo-125M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5483
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: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.5248 | 0.19 | 1000 | 2.9757 |
2.5422 | 0.37 | 2000 | 2.4397 |
2.1642 | 0.56 | 3000 | 2.1880 |
1.9135 | 0.74 | 4000 | 1.9884 |
1.7236 | 0.93 | 5000 | 1.8470 |
1.5459 | 1.11 | 6000 | 1.7501 |
1.4363 | 1.3 | 7000 | 1.6761 |
1.3639 | 1.49 | 8000 | 1.6105 |
1.3046 | 1.67 | 9000 | 1.5667 |
1.273 | 1.86 | 10000 | 1.5483 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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