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albert-offensive-lm-tapt

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

• eval_loss: 0.0001
• eval_runtime: 16.9087
• eval_samples_per_second: 59.141
• eval_steps_per_second: 1.893
• epoch: 0.39
• step: 600

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: 8
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 16
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.23.1
• Pytorch 1.13.0+cu117
• Datasets 2.6.1
• Tokenizers 0.13.1