twscrape-prepared-regression-e5-base-4k

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twscrape-prepared-regression-e5-base-4k

This model is a fine-tuned version of dwzhu/e5-base-4k on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0003
• Mse: 0.0003
• Target 0 Mse: 0.0010
• Target 1 Mse: 0.0003
• Target 2 Mse: 0.0001
• Target 3 Mse: 0.0000

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: 32
• eval_batch_size: 32
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 256
• total_eval_batch_size: 256
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10.0

Training results

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1+cu124
• Datasets 3.0.1
• Tokenizers 0.21.0