---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
base_model: distilbert-base-uncased-finetuned-sst-2-english
model-index:
- name: soft-search
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# soft-search

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5558
- F1: 0.5960
- Accuracy: 0.7109
- Precision: 0.5769
- Recall: 0.6164

## 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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
| 0.5939        | 1.0   | 71   | 0.5989          | 0.0533 | 0.6635   | 1.0       | 0.0274 |
| 0.5903        | 2.0   | 142  | 0.5558          | 0.5960 | 0.7109   | 0.5769    | 0.6164 |
| 0.4613        | 3.0   | 213  | 0.6670          | 0.5641 | 0.6777   | 0.5301    | 0.6027 |
| 0.4454        | 4.0   | 284  | 0.7647          | 0.5541 | 0.6872   | 0.5467    | 0.5616 |
| 0.2931        | 5.0   | 355  | 0.8726          | 0.5139 | 0.6682   | 0.5211    | 0.5068 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2