|
--- |
|
library_name: transformers |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- kanishka/babylm2-clean |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: opt-babylm2-clean-20-epochs-earlystop_seed-42_1e-3 |
|
results: |
|
- task: |
|
name: Causal Language Modeling |
|
type: text-generation |
|
dataset: |
|
name: kanishka/babylm2-clean |
|
type: kanishka/babylm2-clean |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.46725332517112805 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# opt-babylm2-clean-20-epochs-earlystop_seed-42_1e-3 |
|
|
|
This model was trained from scratch on the kanishka/babylm2-clean dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.7611 |
|
- Accuracy: 0.4673 |
|
|
|
## 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: 0.001 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 256 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 32000 |
|
- num_epochs: 20.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-------:|:-----:|:---------------:|:--------:| |
|
| 4.24 | 0.9998 | 2198 | 3.9528 | 0.3447 | |
|
| 3.5581 | 2.0 | 4397 | 3.4120 | 0.3948 | |
|
| 3.2191 | 2.9998 | 6595 | 3.1806 | 0.4180 | |
|
| 3.0495 | 4.0 | 8794 | 3.0720 | 0.4287 | |
|
| 2.9458 | 4.9998 | 10992 | 3.0054 | 0.4354 | |
|
| 2.8669 | 6.0 | 13191 | 2.9663 | 0.4399 | |
|
| 2.8256 | 6.9998 | 15389 | 2.9382 | 0.4430 | |
|
| 2.79 | 8.0 | 17588 | 2.9199 | 0.4452 | |
|
| 2.7624 | 8.9998 | 19786 | 2.9052 | 0.4468 | |
|
| 2.7361 | 10.0 | 21985 | 2.8915 | 0.4482 | |
|
| 2.7354 | 10.9998 | 24183 | 2.8843 | 0.4491 | |
|
| 2.7225 | 12.0 | 26382 | 2.8777 | 0.4500 | |
|
| 2.7092 | 12.9998 | 28580 | 2.8708 | 0.4505 | |
|
| 2.6987 | 14.0 | 30779 | 2.8688 | 0.4509 | |
|
| 2.6894 | 14.9998 | 32977 | 2.8542 | 0.4527 | |
|
| 2.6561 | 16.0 | 35176 | 2.8258 | 0.4564 | |
|
| 2.6055 | 16.9998 | 37374 | 2.8005 | 0.4595 | |
|
| 2.5464 | 18.0 | 39573 | 2.7814 | 0.4627 | |
|
| 2.4778 | 18.9998 | 41771 | 2.7630 | 0.4658 | |
|
| 2.4036 | 19.9955 | 43960 | 2.7611 | 0.4673 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.1 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.0 |
|
|
