README.md

---
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: 0.7255275697753574
---

<!-- 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: 1.2799
- Accuracy: 0.7255

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3784        | 1.0   | 150  | 1.2822          | 0.7290   |
| 1.3804        | 2.0   | 300  | 1.2755          | 0.7273   |
| 1.3586        | 3.0   | 450  | 1.2628          | 0.7288   |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3