metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentence-compression
results: []
sentence-compression
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3786
- Accuracy: 0.8322
- F1: 0.7306
- Precision: 0.7399
- Recall: 0.7215
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6327 | 1.0 | 50 | 0.5976 | 0.7034 | 0.1331 | 0.8506 | 0.0722 |
| 0.5127 | 2.0 | 100 | 0.4569 | 0.7883 | 0.6009 | 0.7411 | 0.5054 |
| 0.42 | 3.0 | 150 | 0.3786 | 0.8322 | 0.7306 | 0.7399 | 0.7215 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3