README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
base_model: albert-large-v2
model-index:
  - name: albert-large-v2-finetuned-rte
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          args: rte
        metrics:
          - type: accuracy
            value: 0.5487364620938628
            name: Accuracy

albert-large-v2-finetuned-rte

This model is a fine-tuned version of albert-large-v2 on the glue dataset. It achieves the following results on the evaluation set:

• Loss: 0.6827
• Accuracy: 0.5487

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	18	0.6954	0.5271
No log	2.0	36	0.6860	0.5379
No log	3.0	54	0.6827	0.5487
No log	4.0	72	0.7179	0.5235
No log	5.0	90	0.7504	0.5379

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.18.1
• Tokenizers 0.10.3