---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: trainer7
  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. -->

# trainer7

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: 1.3387
- Precision: 0.7247
- Recall: 0.6905
- F1: 0.6847
- Accuracy: 0.6905

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8743        | 0.57  | 30   | 1.7616          | 0.1668    | 0.2857 | 0.1788 | 0.2857   |
| 1.7125        | 1.13  | 60   | 1.6249          | 0.2572    | 0.3810 | 0.2914 | 0.3810   |
| 1.4398        | 1.7   | 90   | 1.3244          | 0.4911    | 0.4881 | 0.4326 | 0.4881   |
| 1.0265        | 2.26  | 120  | 1.0496          | 0.6570    | 0.6429 | 0.6197 | 0.6429   |
| 0.6366        | 2.83  | 150  | 0.9035          | 0.6304    | 0.5952 | 0.5764 | 0.5952   |
| 0.3959        | 3.4   | 180  | 0.8226          | 0.6881    | 0.6667 | 0.6557 | 0.6667   |
| 0.2172        | 3.96  | 210  | 1.0152          | 0.6932    | 0.6429 | 0.6356 | 0.6429   |
| 0.0946        | 4.53  | 240  | 1.0485          | 0.7357    | 0.6786 | 0.6913 | 0.6786   |
| 0.0416        | 5.09  | 270  | 1.1458          | 0.6983    | 0.6548 | 0.6565 | 0.6548   |
| 0.0238        | 5.66  | 300  | 1.4215          | 0.6839    | 0.6310 | 0.6272 | 0.6310   |
| 0.0132        | 6.23  | 330  | 1.2009          | 0.7481    | 0.7024 | 0.7090 | 0.7024   |
| 0.0077        | 6.79  | 360  | 1.2686          | 0.6968    | 0.6548 | 0.6538 | 0.6548   |
| 0.0064        | 7.36  | 390  | 1.2725          | 0.7128    | 0.6786 | 0.6717 | 0.6786   |
| 0.0057        | 7.92  | 420  | 1.3092          | 0.7161    | 0.6786 | 0.6731 | 0.6786   |
| 0.0053        | 8.49  | 450  | 1.3306          | 0.7065    | 0.6667 | 0.6640 | 0.6667   |
| 0.0046        | 9.06  | 480  | 1.3377          | 0.7156    | 0.6786 | 0.6749 | 0.6786   |
| 0.0044        | 9.62  | 510  | 1.3387          | 0.7247    | 0.6905 | 0.6847 | 0.6905   |


### Framework versions

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