---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer8
  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. -->

# trainer8

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: 1.6219
- Precision: 0.6754
- Recall: 0.6190
- F1: 0.6211
- Accuracy: 0.6190

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8672        | 0.57  | 30   | 1.7381          | 0.3395    | 0.3810 | 0.2691 | 0.3810   |
| 1.5788        | 1.13  | 60   | 1.4116          | 0.3983    | 0.5    | 0.4344 | 0.5      |
| 1.1325        | 1.7   | 90   | 1.1528          | 0.6029    | 0.6071 | 0.5755 | 0.6071   |
| 0.7556        | 2.26  | 120  | 0.8986          | 0.6796    | 0.6310 | 0.6237 | 0.6310   |
| 0.458         | 2.83  | 150  | 0.9989          | 0.6815    | 0.6071 | 0.5981 | 0.6071   |
| 0.2407        | 3.4   | 180  | 1.2074          | 0.6018    | 0.5476 | 0.5200 | 0.5476   |
| 0.2018        | 3.96  | 210  | 1.0334          | 0.7163    | 0.6786 | 0.6847 | 0.6786   |
| 0.0545        | 4.53  | 240  | 1.2405          | 0.6544    | 0.5952 | 0.5899 | 0.5952   |
| 0.0464        | 5.09  | 270  | 1.1513          | 0.7442    | 0.6905 | 0.6869 | 0.6905   |
| 0.0105        | 5.66  | 300  | 1.5555          | 0.7304    | 0.6429 | 0.6344 | 0.6429   |
| 0.025         | 6.23  | 330  | 1.3049          | 0.7119    | 0.6310 | 0.6343 | 0.6310   |
| 0.0045        | 6.79  | 360  | 1.3200          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0036        | 7.36  | 390  | 1.4460          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0031        | 7.92  | 420  | 1.4770          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0028        | 8.49  | 450  | 1.4846          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0023        | 9.06  | 480  | 1.5149          | 0.6666    | 0.6071 | 0.6086 | 0.6071   |
| 0.0022        | 9.62  | 510  | 1.5523          | 0.6666    | 0.6071 | 0.6086 | 0.6071   |
| 0.002         | 10.19 | 540  | 1.5883          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0019        | 10.75 | 570  | 1.6123          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0016        | 11.32 | 600  | 1.6183          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0017        | 11.89 | 630  | 1.6112          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0016        | 12.45 | 660  | 1.6067          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0015        | 13.02 | 690  | 1.6122          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0014        | 13.58 | 720  | 1.6163          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0014        | 14.15 | 750  | 1.6194          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |
| 0.0015        | 14.72 | 780  | 1.6215          | 0.6754    | 0.6190 | 0.6211 | 0.6190   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2