File size: 2,882 Bytes
0a3f082 |
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 |
---
library_name: transformers
license: mit
base_model: openai-community/gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clm-gpt2
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. -->
# clm-gpt2
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5054
- Accuracy: 0.6325
## 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: 0.003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.4536 | 0.1302 | 500 | 2.1316 | 0.4955 |
| 2.1054 | 0.2603 | 1000 | 2.0124 | 0.5221 |
| 1.9756 | 0.3905 | 1500 | 1.9025 | 0.5453 |
| 1.8863 | 0.5206 | 2000 | 1.8367 | 0.5601 |
| 1.8283 | 0.6508 | 2500 | 1.7927 | 0.5686 |
| 1.7893 | 0.7809 | 3000 | 1.7585 | 0.5760 |
| 1.7555 | 0.9111 | 3500 | 1.7328 | 0.5815 |
| 1.7143 | 1.0413 | 4000 | 1.7016 | 0.5882 |
| 1.6697 | 1.1714 | 4500 | 1.6813 | 0.5930 |
| 1.6584 | 1.3016 | 5000 | 1.6615 | 0.5972 |
| 1.6438 | 1.4317 | 5500 | 1.6422 | 0.6009 |
| 1.6184 | 1.5619 | 6000 | 1.6236 | 0.6049 |
| 1.6086 | 1.6920 | 6500 | 1.6102 | 0.6082 |
| 1.5882 | 1.8222 | 7000 | 1.5938 | 0.6114 |
| 1.5719 | 1.9524 | 7500 | 1.5786 | 0.6148 |
| 1.5272 | 2.0825 | 8000 | 1.5718 | 0.6175 |
| 1.4971 | 2.2127 | 8500 | 1.5593 | 0.6204 |
| 1.4893 | 2.3428 | 9000 | 1.5475 | 0.6227 |
| 1.4808 | 2.4730 | 9500 | 1.5382 | 0.6251 |
| 1.4689 | 2.6031 | 10000 | 1.5274 | 0.6275 |
| 1.4572 | 2.7333 | 10500 | 1.5169 | 0.6298 |
| 1.4488 | 2.8635 | 11000 | 1.5106 | 0.6315 |
| 1.4465 | 2.9936 | 11500 | 1.5054 | 0.6325 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|