README.md

metadata

license: apache-2.0
base_model: t5-large
tags:
  - generated_from_trainer
datasets:
  - super_glue
metrics:
  - accuracy
model-index:
  - name: t5-large_wic_dense_epochs-5
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: super_glue
          type: super_glue
          config: wic
          split: validation
          args: wic
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6598746081504702

t5-large_wic_dense_epochs-5

This model is a fine-tuned version of t5-large on the super_glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.7106
• Accuracy: 0.6599

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: 64
• eval_batch_size: 64
• seed: 0
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 20
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6058	2.35	50	0.7125	0.6176
0.4662	4.71	100	0.7054	0.6614

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1