---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: sentence-compression
  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. -->

# sentence-compression

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4221
- Accuracy: 0.8121
- F1: 0.7275
- Precision: 0.7317
- Recall: 0.7233

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6263        | 1.0   | 50   | 0.6252          | 0.6549   | 0.0183 | 0.6667    | 0.0093 |
| 0.4727        | 2.0   | 100  | 0.4900          | 0.7805   | 0.6472 | 0.7309    | 0.5807 |
| 0.4053        | 3.0   | 150  | 0.4221          | 0.8121   | 0.7275 | 0.7317    | 0.7233 |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Tokenizers 0.10.3