metadata
base_model: princeton-nlp/sup-simcse-roberta-large
tags:
- generated_from_trainer
metrics:
- pearsonr
- spearmanr
model-index:
- name: enc_bi_encoder__lr_1e-5__wd_0.1__trans_False__obj_mse__tri_None__s_42
results: []
enc_bi_encoder__lr_1e-5__wd_0.1__trans_False__obj_mse__tri_None__s_42
This model is a fine-tuned version of princeton-nlp/sup-simcse-roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0951
- Mse: 0.0951
- Pearsonr: 0.4802
- Spearmanr: 0.4799
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: 1e-05
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Pearsonr | Spearmanr |
|---|---|---|---|---|---|---|
| No log | 1.0 | 354 | 0.0973 | 0.0973 | 0.4643 | 0.4659 |
| 0.0949 | 2.0 | 709 | 0.0964 | 0.0964 | 0.4691 | 0.4692 |
| 0.0785 | 3.0 | 1062 | 0.0951 | 0.0951 | 0.4802 | 0.4799 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.1