---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
metrics:
- accuracy
model-index:
- name: bert_base_rand_100_v2
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
      type: Hartunka/processed_wikitext-103-raw-v1-rand-100_v2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.15335932643950953
---

<!-- 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. -->

# bert_base_rand_100_v2

This model is a fine-tuned version of [](https://huggingface.co/) on the Hartunka/processed_wikitext-103-raw-v1-rand-100_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 10.7777
- Accuracy: 0.1534

## 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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 10.6199       | 4.1982  | 10000 | 10.7772         | 0.1509   |
| 9.3028        | 8.3963  | 20000 | 11.4804         | 0.1521   |
| 7.6531        | 12.5945 | 30000 | 12.8492         | 0.1543   |
| 6.6672        | 16.7926 | 40000 | 13.9831         | 0.1512   |
| 6.3804        | 20.9908 | 50000 | 14.2044         | 0.1516   |


### Framework versions

- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1