Weave Local Scorers
Collection
Locally runnable models as described in the Weave documentation here: https://weave-docs.wandb.ai/guides/evaluation/weave_local_scorers
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7 items
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Updated
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
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Model tree for wandb/WeaveContextRelevanceScorerV1
Base model
microsoft/deberta-v3-base
Finetuned
tasksource/deberta-base-long-nli