|
|
--- |
|
|
library_name: transformers |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- bleu |
|
|
model-index: |
|
|
- name: rotating-head-gp-norm-gpt2-medium-wikitext |
|
|
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. --> |
|
|
|
|
|
# rotating-head-gp-norm-gpt2-medium-wikitext |
|
|
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 3.2113 |
|
|
- Accuracy: 0.4180 |
|
|
- Perplexity: 24.8108 |
|
|
- Bleu: 0.1307 |
|
|
|
|
|
## 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: 0.0001 |
|
|
- train_batch_size: 64 |
|
|
- eval_batch_size: 64 |
|
|
- seed: 42 |
|
|
- 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: linear |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 5 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Perplexity | Bleu | |
|
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:| |
|
|
| 5.9057 | 0.2806 | 500 | 5.7484 | 0.2234 | 313.6789 | 0.0477 | |
|
|
| 4.8613 | 0.5612 | 1000 | 4.7455 | 0.2807 | 115.0632 | 0.0711 | |
|
|
| 4.2976 | 0.8418 | 1500 | 4.2220 | 0.3187 | 68.1694 | 0.0837 | |
|
|
| 3.9568 | 1.1223 | 2000 | 3.9271 | 0.3461 | 50.7582 | 0.0934 | |
|
|
| 3.7919 | 1.4029 | 2500 | 3.7617 | 0.3626 | 43.0211 | 0.0942 | |
|
|
| 3.692 | 1.6835 | 3000 | 3.6573 | 0.3725 | 38.7561 | 0.1052 | |
|
|
| 3.5939 | 1.9641 | 3500 | 3.5628 | 0.3818 | 35.2616 | 0.1094 | |
|
|
| 3.483 | 2.2447 | 4000 | 3.4932 | 0.3879 | 32.8924 | 0.1140 | |
|
|
| 3.4251 | 2.5253 | 4500 | 3.4391 | 0.3933 | 31.1583 | 0.1204 | |
|
|
| 3.3876 | 2.8058 | 5000 | 3.3855 | 0.3991 | 29.5323 | 0.1227 | |
|
|
| 3.2719 | 3.0864 | 5500 | 3.3499 | 0.4020 | 28.5004 | 0.1246 | |
|
|
| 3.2612 | 3.3670 | 6000 | 3.3160 | 0.4062 | 27.5488 | 0.1283 | |
|
|
| 3.2373 | 3.6476 | 6500 | 3.2848 | 0.4095 | 26.7034 | 0.1288 | |
|
|
| 3.2086 | 3.9282 | 7000 | 3.2598 | 0.4118 | 26.0453 | 0.1297 | |
|
|
| 3.1402 | 4.2088 | 7500 | 3.2398 | 0.4146 | 25.5281 | 0.1344 | |
|
|
| 3.1002 | 4.4893 | 8000 | 3.2246 | 0.4162 | 25.1447 | 0.1317 | |
|
|
| 3.1099 | 4.7699 | 8500 | 3.2113 | 0.4180 | 24.8108 | 0.1307 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.49.0 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.3.2 |
|
|
- Tokenizers 0.21.0 |
|
|
|
