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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
model-index:
- name: mlm
results:
- task:
name: Masked Language Modeling
type: fill-mask
dataset:
name: wikitext wikitext-2-raw-v1
type: wikitext
config: wikitext-2-raw-v1
split: validation
args: wikitext-2-raw-v1
metrics:
- name: Accuracy
type: accuracy
value: 0.7302927161334241
---
<!-- 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. -->
# mlm
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the wikitext wikitext-2-raw-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2468
- Accuracy: 0.7303
## 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: 8
- eval_batch_size: 8
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3758 | 1.0 | 150 | 1.2826 | 0.7277 |
| 1.3763 | 2.0 | 300 | 1.2747 | 0.7272 |
| 1.3558 | 3.0 | 450 | 1.2607 | 0.7278 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|