intfloat-e5-base-v2-english-fp16-allagree

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intfloat-e5-base-v2-english-fp16-allagree

This model is a fine-tuned version of intfloat/e5-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1038
• Accuracy: 0.9780
• Precision: 0.9779
• Recall: 0.9780
• F1: 0.9779

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.3
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.48.2
• Pytorch 2.6.0+cu124
• Datasets 3.3.1
• Tokenizers 0.21.0