Instructions to use muhtasham/tiny-mlm-wikitext-from-scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhtasham/tiny-mlm-wikitext-from-scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="muhtasham/tiny-mlm-wikitext-from-scratch")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("muhtasham/tiny-mlm-wikitext-from-scratch") model = AutoModelForMaskedLM.from_pretrained("muhtasham/tiny-mlm-wikitext-from-scratch") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: tiny-mlm-wikitext-from-scratch | |
| 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. --> | |
| # tiny-mlm-wikitext-from-scratch | |
| This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: nan | |
| ## 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: 3e-05 | |
| - train_batch_size: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: constant | |
| - training_steps: 5000 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 9.4738 | 0.4 | 500 | 8.8348 | | |
| | 8.3457 | 0.8 | 1000 | 8.1343 | | |
| | 7.8654 | 1.2 | 1500 | nan | | |
| | 7.7136 | 1.6 | 2000 | 7.9122 | | |
| | 7.6903 | 2.0 | 2500 | 7.8458 | | |
| | 7.6397 | 2.4 | 3000 | 7.8610 | | |
| | 7.6227 | 2.8 | 3500 | 7.8522 | | |
| | 7.5991 | 3.2 | 4000 | nan | | |
| ### Framework versions | |
| - Transformers 4.26.0.dev0 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.8.1.dev0 | |
| - Tokenizers 0.13.2 | |