File size: 4,163 Bytes
4cf9266 ea5a7f8 4cf9266 ea5a7f8 4cf9266 6969cd8 4cf9266 6969cd8 4cf9266 6969cd8 4cf9266 6969cd8 4cf9266 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 |
---
library_name: peft
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: Se124M100KInfPrompt_endtoken2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Se124M100KInfPrompt_endtoken2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6709
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.8989 | 1.0 | 267 | 0.7585 |
| 0.7706 | 2.0 | 534 | 0.7264 |
| 0.7441 | 3.0 | 801 | 0.7160 |
| 0.7327 | 4.0 | 1068 | 0.7091 |
| 0.7175 | 5.0 | 1335 | 0.7024 |
| 0.7118 | 6.0 | 1602 | 0.6990 |
| 0.7079 | 7.0 | 1869 | 0.6931 |
| 0.6982 | 8.0 | 2136 | 0.6904 |
| 0.6977 | 9.0 | 2403 | 0.6891 |
| 0.6971 | 10.0 | 2670 | 0.6869 |
| 0.6992 | 11.0 | 2937 | 0.6850 |
| 0.6889 | 12.0 | 3204 | 0.6849 |
| 0.6924 | 13.0 | 3471 | 0.6845 |
| 0.6894 | 14.0 | 3738 | 0.6834 |
| 0.6886 | 15.0 | 4005 | 0.6791 |
| 0.6906 | 16.0 | 4272 | 0.6812 |
| 0.6868 | 17.0 | 4539 | 0.6796 |
| 0.6852 | 18.0 | 4806 | 0.6789 |
| 0.6797 | 19.0 | 5073 | 0.6784 |
| 0.6813 | 20.0 | 5340 | 0.6775 |
| 0.6823 | 21.0 | 5607 | 0.6776 |
| 0.6803 | 22.0 | 5874 | 0.6758 |
| 0.6782 | 23.0 | 6141 | 0.6768 |
| 0.6786 | 24.0 | 6408 | 0.6747 |
| 0.677 | 25.0 | 6675 | 0.6740 |
| 0.68 | 26.0 | 6942 | 0.6742 |
| 0.6733 | 27.0 | 7209 | 0.6735 |
| 0.6744 | 28.0 | 7476 | 0.6734 |
| 0.6746 | 29.0 | 7743 | 0.6737 |
| 0.674 | 30.0 | 8010 | 0.6753 |
| 0.6694 | 31.0 | 8277 | 0.6731 |
| 0.6731 | 32.0 | 8544 | 0.6734 |
| 0.6683 | 33.0 | 8811 | 0.6723 |
| 0.6712 | 34.0 | 9078 | 0.6723 |
| 0.668 | 35.0 | 9345 | 0.6720 |
| 0.6647 | 36.0 | 9612 | 0.6723 |
| 0.664 | 37.0 | 9879 | 0.6713 |
| 0.6707 | 38.0 | 10146 | 0.6724 |
| 0.6704 | 39.0 | 10413 | 0.6715 |
| 0.6675 | 40.0 | 10680 | 0.6715 |
| 0.6673 | 41.0 | 10947 | 0.6718 |
| 0.6656 | 42.0 | 11214 | 0.6713 |
| 0.6659 | 43.0 | 11481 | 0.6715 |
| 0.667 | 44.0 | 11748 | 0.6714 |
| 0.6596 | 45.0 | 12015 | 0.6709 |
| 0.6673 | 46.0 | 12282 | 0.6710 |
| 0.6666 | 47.0 | 12549 | 0.6710 |
| 0.6661 | 48.0 | 12816 | 0.6709 |
| 0.6637 | 49.0 | 13083 | 0.6709 |
| 0.665 | 49.8143 | 13300 | 0.6709 |
### Framework versions
- PEFT 0.15.1
- Transformers 4.51.3
- Pytorch 2.6.0+cu118
- Datasets 3.5.0
- Tokenizers 0.21.1 |