README.md

metadata

language:
  - en
license: apache-2.0
base_model: JackFram/llama-160m
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: llama-160m-qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5149185429251327

llama-160m-qnli

This model is a fine-tuned version of JackFram/llama-160m on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

• Loss: 0.8172
• Accuracy: 0.5149

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5.0

Training results

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.18.0
• Tokenizers 0.13.3