metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - bigbench
metrics:
  - accuracy
model-index:
  - name: bigbench_entailedpolarity-bert-base-uncased
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: bigbench
          type: bigbench
          config: entailed_polarity
          split: train
          args: entailed_polarity
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9583333333333334

bigbench_entailedpolarity-bert-base-uncased

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

Loss: 0.3706
Accuracy: 0.9583

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: 4
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	24	0.5613	0.7917
No log	2.0	48	0.5337	0.7917
No log	3.0	72	0.3178	0.875
No log	4.0	96	0.1924	0.9167
No log	5.0	120	0.2007	0.9583
No log	6.0	144	0.2766	0.9583
No log	7.0	168	0.3031	0.9583
No log	8.0	192	0.3291	0.9583
No log	9.0	216	0.3381	0.9583
No log	10.0	240	0.3454	0.9583
No log	11.0	264	0.3508	0.9583
No log	12.0	288	0.3554	0.9583
No log	13.0	312	0.3592	0.9583
No log	14.0	336	0.3624	0.9583
No log	15.0	360	0.3650	0.9583
No log	16.0	384	0.3671	0.9583
No log	17.0	408	0.3686	0.9583
No log	18.0	432	0.3696	0.9583
No log	19.0	456	0.3704	0.9583
No log	20.0	480	0.3706	0.9583

Framework versions

Transformers 4.35.2
Pytorch 1.10.1+cu102
Datasets 2.15.0
Tokenizers 0.15.0