README.md

metadata

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

usclm-distilbert-base-uncased-mk1

This model is a fine-tuned version of 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