metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: sentence_bert-base-uncased-finetuned-SENTENCE
results: []
sentence_bert-base-uncased-finetuned-SENTENCE
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4834
- Precision: 0.8079
- Recall: 1.0
- F1: 0.8938
- Accuracy: 0.8079
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 13 | 0.3520 | 0.8889 | 1.0 | 0.9412 | 0.8889 |
| No log | 2.0 | 26 | 0.3761 | 0.8889 | 1.0 | 0.9412 | 0.8889 |
| No log | 3.0 | 39 | 0.3683 | 0.8889 | 1.0 | 0.9412 | 0.8889 |
| No log | 4.0 | 52 | 0.3767 | 0.8889 | 1.0 | 0.9412 | 0.8889 |
| No log | 5.0 | 65 | 0.3834 | 0.8889 | 1.0 | 0.9412 | 0.8889 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3