---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-Distilbert-Model
  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. -->

# distilbert-base-uncased-Distilbert-Model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7456
- F1: 0.7245

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8394        | 0.5   | 500  | 0.8400          | 0.6557 |
| 0.7944        | 1.0   | 1000 | 0.7827          | 0.6959 |
| 0.7253        | 1.5   | 1500 | 0.7619          | 0.6763 |
| 0.6838        | 2.01  | 2000 | 0.7456          | 0.7245 |
| 0.5503        | 2.51  | 2500 | 0.7754          | 0.7117 |
| 0.5517        | 3.01  | 3000 | 0.7592          | 0.7199 |
| 0.4178        | 3.51  | 3500 | 0.9776          | 0.7145 |
| 0.4225        | 4.01  | 4000 | 1.1820          | 0.7055 |
| 0.3327        | 4.51  | 4500 | 1.3212          | 0.7038 |
| 0.3292        | 5.02  | 5000 | 1.4429          | 0.7057 |
| 0.2563        | 5.52  | 5500 | 1.5018          | 0.7049 |
| 0.2555        | 6.02  | 6000 | 1.4722          | 0.7025 |
| 0.1745        | 6.52  | 6500 | 1.7254          | 0.7035 |
| 0.1813        | 7.02  | 7000 | 1.7894          | 0.6957 |
| 0.1473        | 7.52  | 7500 | 1.9552          | 0.6947 |
| 0.1381        | 8.02  | 8000 | 1.9619          | 0.7022 |
| 0.1003        | 8.53  | 8500 | 2.0648          | 0.6982 |
| 0.0916        | 9.03  | 9000 | 2.1473          | 0.6945 |
| 0.0779        | 9.53  | 9500 | 2.1930          | 0.6947 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3