---
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: []
---

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# 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](https://huggingface.co/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