fine_tuned_gpt2_clm-model
This model is a fine-tuned version of
gpt2 on the eli5 dataset.
It achieves the following results on the evaluation set:
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-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: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|
| No log | 1.0 | 142 | 3.3422 |
| No log | 2.0 | 284 | 3.3226 |
| No log | 3.0 | 426 | 3.3148 |
| 3.4352 | 4.0 | 568 | 3.3095 |
| 3.4352 | 5.0 | 710 | 3.3074 |
| 3.4352 | 6.0 | 852 | 3.3066 |
| 3.4352 | 7.0 | 994 | 3.3046 |
| 3.3068 | 8.0 | 1136 | 3.3049 |
| 3.3068 | 9.0 | 1278 | 3.3048 |
| 3.3068 | 10.0 | 1420 | 3.3050 |
| 3.2433 | 11.0 | 1562 | 3.3062 |
| 3.2433 | 12.0 | 1704 | 3.3059 |
| 3.2433 | 13.0 | 1846 | 3.3062 |
| 3.2433 | 14.0 | 1988 | 3.3065 |
| 3.2113 | 15.0 | 2130 | 3.3066 |
Inference:
-
prompt = "dna phosphorylation is the process of"
-
generated Text: dna phosphorylation is the process of forming the deoxygenated product. For example, in a protein phosphorylation inhibitor, it occurs to deoxygenate the phosphorylated protein by binding a phosphate molecule and preventing it from being destroyed by a nonenzymatic process.
In a phosphorylation inhibitor like dna, the product is phosphorylated by the phosphocreatine, a phosphorylated phosphocreatine molecule that can bind to other phosphocreatine molecules that bind to phosphocreatine. This interaction helps to separate the phosphocreatine molecule that is phosphorylated from the phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-glucose molecule that is phosphocreatine-phosphocreatine-glucose-phosphocreatine-phosphocreatine-glucose.
In anoxidase inhibitors like dna, they are a bit more specific, more specific, and have a more complicated interaction with the phosphocreatine molecule that can bind to phosphocreatine molecules.
I would argue that both dna-and phosphocreatine-phosphocreatine-glucose will not be able to bind to phosphocreatine because the phosphocreatine-phosphocreatine-phosphocreatine-glucose-phosphocreatine molecule that was phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-glucose, is phosphocreatine.
That is, dna-and phosphocreatine-glucose will be able to bind to phosphocreatine because the phosphocreatine molecule that was phosphocreatine-glucose will not be phosphocreatine because the phosphocreatine-phosphocreatine-glucose molecule that was phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine-glucose, is phosphocreatine.
Edit: Added: The final point is that it can't bind phosphocreatine because that phosphocreatine molecule (a phosphocreatine-phosphocreatine-phosphocreatine-phosphocreatine molecule) can not be phosphoc
Evaluation metric:
Perplexity: 27.29
GPU:
- CUDA Version: 12.1
- 4x Tesla T4
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
