---
tags:
- generated_from_trainer
datasets:
- hyperdemocracy/usc-llm-text
metrics:
- accuracy
model-index:
- name: usclm-distilbert-base-uncased-mk1
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: hyperdemocracy/usc-llm-text
      type: hyperdemocracy/usc-llm-text
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.15919007666071758
---

<!-- 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. -->

# usclm-distilbert-base-uncased-mk1

This model is a fine-tuned version of [](https://huggingface.co/) on the hyperdemocracy/usc-llm-text dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2971
- Accuracy: 0.1592

## 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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2