electra-base-discriminator-CoLA

electra-base-discriminator-CoLA

This model is a fine-tuned version of google/electra-base-discriminator on the GLUE COLA dataset. It achieves the following results on the evaluation set:

• Loss: 0.3542
• Matthews Correlation: 0.6580

Model description

Trying to find a decent optimum between accuracy/quality and inference speed.

{
    "epoch": 8.0,
    "eval_loss": 0.3541961908340454,
    "eval_matthews_correlation": 0.6579677841732349,
    "eval_runtime": 1.9552,
    "eval_samples": 1043,
    "eval_samples_per_second": 533.451,
    "eval_steps_per_second": 33.756
}

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: 8e-05
• train_batch_size: 128
• eval_batch_size: 16
• seed: 22165
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 8.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.8.0
• Tokenizers 0.13.1