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
File size: 1,599 Bytes
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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
|