---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer_2f
  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. -->

# trainer_2f

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6467
- Precision: 0.8276
- Recall: 0.8207
- F1: 0.8208
- Accuracy: 0.8207

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8981        | 0.27  | 30   | 1.7350          | 0.4229    | 0.4146 | 0.3885 | 0.4146   |
| 1.5297        | 0.54  | 60   | 1.3572          | 0.4949    | 0.4286 | 0.3544 | 0.4286   |
| 1.2565        | 0.81  | 90   | 1.0154          | 0.7047    | 0.6891 | 0.6859 | 0.6891   |
| 0.9124        | 1.08  | 120  | 0.8039          | 0.7558    | 0.7535 | 0.7496 | 0.7535   |
| 0.6233        | 1.35  | 150  | 0.6860          | 0.7788    | 0.7731 | 0.7692 | 0.7731   |
| 0.5281        | 1.62  | 180  | 0.6874          | 0.7504    | 0.7395 | 0.7383 | 0.7395   |
| 0.4313        | 1.89  | 210  | 0.6302          | 0.7992    | 0.7899 | 0.7888 | 0.7899   |
| 0.3041        | 2.16  | 240  | 0.6437          | 0.7706    | 0.7619 | 0.7610 | 0.7619   |
| 0.2096        | 2.43  | 270  | 0.6585          | 0.7847    | 0.7759 | 0.7731 | 0.7759   |
| 0.2161        | 2.7   | 300  | 0.6198          | 0.8121    | 0.8039 | 0.8027 | 0.8039   |
| 0.1888        | 2.97  | 330  | 0.6286          | 0.8298    | 0.8207 | 0.8201 | 0.8207   |
| 0.1107        | 3.24  | 360  | 0.6106          | 0.8297    | 0.8263 | 0.8260 | 0.8263   |
| 0.0834        | 3.51  | 390  | 0.6133          | 0.8223    | 0.8179 | 0.8170 | 0.8179   |
| 0.0858        | 3.78  | 420  | 0.6481          | 0.8244    | 0.8179 | 0.8178 | 0.8179   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2