---
license: mit
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
base_model: roberta-base
model-index:
- name: wikitext_roberta-base
  results:
  - task:
      type: fill-mask
      name: Masked Language Modeling
    dataset:
      name: wikitext wikitext-2-raw-v1
      type: wikitext
      args: wikitext-2-raw-v1
    metrics:
    - type: accuracy
      value: 0.7371052344006119
      name: Accuracy
---

<!-- 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. -->

# wikitext_roberta-base

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: 1.2143
- Accuracy: 0.7371

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4175        | 0.99  | 37   | 1.3355          | 0.7194   |
| 1.438         | 1.99  | 74   | 1.2953          | 0.7249   |
| 1.4363        | 2.99  | 111  | 1.2759          | 0.7276   |
| 1.3391        | 3.99  | 148  | 1.2904          | 0.7252   |
| 1.3741        | 4.99  | 185  | 1.2621          | 0.7290   |
| 1.2771        | 5.99  | 222  | 1.2312          | 0.7353   |
| 1.287         | 6.99  | 259  | 1.2542          | 0.7289   |
| 1.29          | 7.99  | 296  | 1.2290          | 0.7345   |
| 1.2948        | 8.99  | 333  | 1.2537          | 0.7286   |
| 1.2741        | 9.99  | 370  | 1.2199          | 0.7354   |
| 1.2342        | 10.99 | 407  | 1.2520          | 0.7309   |
| 1.2199        | 11.99 | 444  | 1.2738          | 0.7260   |
| 1.206         | 12.99 | 481  | 1.2286          | 0.7335   |
| 1.221         | 13.99 | 518  | 1.2421          | 0.7327   |
| 1.2062        | 14.99 | 555  | 1.2402          | 0.7328   |
| 1.2305        | 15.99 | 592  | 1.2473          | 0.7308   |
| 1.2426        | 16.99 | 629  | 1.2250          | 0.7318   |
| 1.2096        | 17.99 | 666  | 1.2186          | 0.7353   |
| 1.1961        | 18.99 | 703  | 1.2214          | 0.7361   |
| 1.2136        | 19.99 | 740  | 1.2506          | 0.7311   |


### Framework versions

- Transformers 4.21.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.3.3.dev0
- Tokenizers 0.12.1