---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer_1
  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_1

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: 4.3044
- Precision: 0.5942
- Recall: 0.5
- F1: 0.5025
- Accuracy: 0.5

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0878        | 0.57  | 30   | 4.2282          | 0.6436    | 0.5714 | 0.5864 | 0.5714   |
| 0.0           | 1.13  | 60   | 4.2780          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 1.7   | 90   | 4.2442          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 2.26  | 120  | 4.2581          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 2.83  | 150  | 4.2636          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 3.4   | 180  | 4.2857          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 3.96  | 210  | 4.2952          | 0.5942    | 0.5    | 0.5025 | 0.5      |
| 0.0           | 4.53  | 240  | 4.3025          | 0.5942    | 0.5    | 0.5025 | 0.5      |


### Framework versions

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