WeaveContextRelevanceScorerV1 – AI Model by wandb | AlphaNeural AI

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wandb/
WeaveContextRelevanceScorerV1

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token-classification

generated_from_trainer

tasksource/deberta-base-long-nli

autotrain_compatible

endpoints_compatible

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deberta-base-long-nli-relevance-token-clf

This model is a fine-tuned version of tasksource/deberta-base-long-nli on an unknown dataset.

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: 12
eval_batch_size: 32
seed: 2024
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 384
total_eval_batch_size: 256
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy	Precision	Recall
No log	0	0	0.2041	0.0	0.0	0.0	0.0

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0