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

# trainerH

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3385
- Precision: 0.8173
- Recall: 0.8123
- F1: 0.8128
- Accuracy: 0.8123

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0142        | 0.14  | 30   | 0.9604          | 0.8284    | 0.8207 | 0.8202 | 0.8207   |
| 0.0446        | 0.27  | 60   | 0.9032          | 0.8403    | 0.8347 | 0.8353 | 0.8347   |
| 0.0995        | 0.41  | 90   | 1.0133          | 0.8310    | 0.8263 | 0.8258 | 0.8263   |
| 0.0776        | 0.54  | 120  | 1.1968          | 0.8130    | 0.7983 | 0.7961 | 0.7983   |
| 0.0517        | 0.68  | 150  | 1.1238          | 0.8363    | 0.8263 | 0.8263 | 0.8263   |
| 0.1014        | 0.81  | 180  | 1.0750          | 0.8334    | 0.8291 | 0.8293 | 0.8291   |
| 0.1166        | 0.95  | 210  | 1.1253          | 0.8009    | 0.7955 | 0.7955 | 0.7955   |
| 0.0447        | 1.08  | 240  | 1.2334          | 0.7969    | 0.7899 | 0.7883 | 0.7899   |
| 0.0411        | 1.22  | 270  | 1.1707          | 0.8369    | 0.8319 | 0.8324 | 0.8319   |
| 0.1145        | 1.35  | 300  | 1.3773          | 0.8320    | 0.8039 | 0.8021 | 0.8039   |
| 0.06          | 1.49  | 330  | 1.1480          | 0.8320    | 0.8291 | 0.8274 | 0.8291   |
| 0.0622        | 1.62  | 360  | 1.0856          | 0.8252    | 0.8235 | 0.8235 | 0.8235   |
| 0.0366        | 1.76  | 390  | 1.2860          | 0.8236    | 0.8151 | 0.8162 | 0.8151   |
| 0.0565        | 1.89  | 420  | 1.2558          | 0.8116    | 0.8011 | 0.8024 | 0.8011   |
| 0.0019        | 2.03  | 450  | 1.2740          | 0.8208    | 0.8179 | 0.8180 | 0.8179   |
| 0.0024        | 2.16  | 480  | 1.3075          | 0.8201    | 0.8151 | 0.8155 | 0.8151   |
| 0.024         | 2.3   | 510  | 1.3170          | 0.8188    | 0.8151 | 0.8154 | 0.8151   |
| 0.0008        | 2.43  | 540  | 1.3992          | 0.8099    | 0.8011 | 0.8024 | 0.8011   |
| 0.0445        | 2.57  | 570  | 1.2633          | 0.8237    | 0.8207 | 0.8209 | 0.8207   |
| 0.01          | 2.7   | 600  | 1.2843          | 0.8270    | 0.8235 | 0.8235 | 0.8235   |
| 0.0175        | 2.84  | 630  | 1.2997          | 0.8246    | 0.8207 | 0.8208 | 0.8207   |
| 0.0111        | 2.97  | 660  | 1.3486          | 0.8147    | 0.8095 | 0.8099 | 0.8095   |
| 0.0006        | 3.11  | 690  | 1.3543          | 0.8154    | 0.8123 | 0.8120 | 0.8123   |
| 0.0005        | 3.24  | 720  | 1.3493          | 0.8185    | 0.8151 | 0.8148 | 0.8151   |
| 0.0129        | 3.38  | 750  | 1.3294          | 0.8136    | 0.8095 | 0.8098 | 0.8095   |
| 0.0005        | 3.51  | 780  | 1.3441          | 0.8143    | 0.8095 | 0.8100 | 0.8095   |
| 0.0005        | 3.65  | 810  | 1.3428          | 0.8143    | 0.8095 | 0.8100 | 0.8095   |
| 0.0005        | 3.78  | 840  | 1.3402          | 0.8173    | 0.8123 | 0.8128 | 0.8123   |
| 0.0005        | 3.92  | 870  | 1.3395          | 0.8173    | 0.8123 | 0.8128 | 0.8123   |


### Framework versions

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