---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- Hartunka/processed_wikitext-103-raw-v1-km-100_v2
metrics:
- accuracy
model-index:
- name: distilbert_km_100_v2
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: Hartunka/processed_wikitext-103-raw-v1-km-100_v2
      type: Hartunka/processed_wikitext-103-raw-v1-km-100_v2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.15431994123297735
---

<!-- 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. -->

# distilbert_km_100_v2

This model is a fine-tuned version of [](https://huggingface.co/) on the Hartunka/processed_wikitext-103-raw-v1-km-100_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 7.0274
- Accuracy: 0.1543

## 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 7.039         | 4.1982  | 10000 | 7.2284          | 0.1497   |
| 6.5358        | 8.3963  | 20000 | 7.0446          | 0.1528   |
| 6.2663        | 12.5945 | 30000 | 7.2460          | 0.1541   |
| 6.1164        | 16.7926 | 40000 | 7.4136          | 0.1521   |
| 6.0315        | 20.9908 | 50000 | 7.3543          | 0.1515   |


### Framework versions

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