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mystv0_abbs
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8311
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
- distributed_type: multi-GPU
- 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: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3179 | 5.12 | 1000 | 1.4846 |
| 1.0028 | 10.24 | 2000 | 1.3123 |
| 0.997 | 15.36 | 3000 | 1.4747 |
| 0.9951 | 20.47 | 4000 | 1.5312 |
| 0.9936 | 25.59 | 5000 | 1.5280 |
| 0.9922 | 30.71 | 6000 | 1.6307 |
| 0.9906 | 35.83 | 7000 | 1.5866 |
| 0.9907 | 40.95 | 8000 | 1.5732 |
| 0.989 | 46.07 | 9000 | 1.4607 |
| 0.9883 | 51.18 | 10000 | 1.4982 |
| 0.9875 | 56.3 | 11000 | 1.4993 |
| 0.9865 | 61.42 | 12000 | 1.6250 |
| 0.9859 | 66.54 | 13000 | 1.5613 |
| 0.9847 | 71.66 | 14000 | 1.7067 |
| 0.9841 | 76.78 | 15000 | 1.6076 |
| 0.9833 | 81.89 | 16000 | 1.6163 |
| 0.9824 | 87.01 | 17000 | 1.6662 |
| 0.9813 | 92.13 | 18000 | 1.4881 |
| 0.9806 | 97.25 | 19000 | 1.5930 |
| 0.9799 | 102.37 | 20000 | 1.6575 |
| 0.9789 | 107.49 | 21000 | 1.7150 |
| 0.9778 | 112.6 | 22000 | 1.6655 |
| 0.9771 | 117.72 | 23000 | 1.7227 |
| 0.976 | 122.84 | 24000 | 1.6713 |
| 0.9749 | 127.96 | 25000 | 1.7268 |
| 0.9738 | 133.08 | 26000 | 1.6831 |
| 0.9725 | 138.2 | 27000 | 1.7084 |
| 0.9714 | 143.31 | 28000 | 1.6809 |
| 0.9697 | 148.43 | 29000 | 1.7715 |
| 0.9683 | 153.55 | 30000 | 1.7643 |
| 0.9668 | 158.67 | 31000 | 1.8609 |
| 0.9654 | 163.79 | 32000 | 1.8082 |
| 0.964 | 168.91 | 33000 | 1.8623 |
| 0.9627 | 174.02 | 34000 | 1.8146 |
| 0.9617 | 179.14 | 35000 | 1.8173 |
| 0.9609 | 184.26 | 36000 | 1.8237 |
| 0.9604 | 189.38 | 37000 | 1.8314 |
| 0.9601 | 194.5 | 38000 | 1.8316 |
| 0.96 | 199.62 | 39000 | 1.8311 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3
