metadata
license: mit
base_model: microsoft/deberta-v3-large
tags:
- generated_from_trainer
metrics:
- pearsonr
- spearmanr
model-index:
- name: enc_cross_encoder__lr_7e-6__wd_0.1__trans_False__obj_mse__tri_None__s_42
results: []
enc_cross_encoder__lr_7e-6__wd_0.1__trans_False__obj_mse__tri_None__s_42
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0917
- Mse: 0.0917
- Pearsonr: 0.4893
- Spearmanr: 0.4924
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: 7e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Pearsonr | Spearmanr |
|---|---|---|---|---|---|---|
| No log | 1.0 | 354 | 0.0982 | 0.0982 | 0.3975 | 0.4064 |
| 0.1166 | 2.0 | 709 | 0.0880 | 0.0880 | 0.4867 | 0.4889 |
| 0.0903 | 3.0 | 1062 | 0.0917 | 0.0917 | 0.4893 | 0.4924 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1
- Datasets 2.19.1
- Tokenizers 0.15.2