README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - multi_nli
metrics:
  - accuracy
model-index:
  - name: nli-finetune-model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: multi_nli
          type: multi_nli
          config: default
          split: validation_matched
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7793333333333333

nli-finetune-model

This model is a fine-tuned version of bert-large-uncased on the multi_nli dataset. It achieves the following results on the evaluation set:

• Loss: 1.2551
• Accuracy: 0.7793

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: 1e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6813	1.0	2500	0.6655	0.7657
0.5632	2.0	5000	1.0409	0.778
0.3753	3.0	7500	1.2551	0.7793

Framework versions

• Transformers 4.28.0
• Pytorch 1.13.1+cu117
• Datasets 2.12.0
• Tokenizers 0.13.3