metadata
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: []
soft-search
This model is a fine-tuned version of 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