---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: My_Model
  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. -->

# My_Model

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4353
- Accuracy@en: 0.8946
- F1@en: 0.8931
- Precision@en: 0.8965
- Recall@en: 0.8952
- Loss@en: 0.4353

## 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: 1e-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 | Accuracy@en | F1@en  | Precision@en | Recall@en | Loss@en |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|:------------:|:---------:|:-------:|
| 3.1352        | 1.0   | 700  | 2.5257          | 0.3279      | 0.2574 | 0.3241       | 0.3350    | 2.5257  |
| 2.1929        | 2.0   | 1400 | 1.6830          | 0.6121      | 0.5597 | 0.6589       | 0.6125    | 1.6830  |
| 1.4355        | 3.0   | 2100 | 1.0143          | 0.7929      | 0.7750 | 0.7990       | 0.7914    | 1.0143  |
| 0.9043        | 4.0   | 2800 | 0.6990          | 0.8242      | 0.8062 | 0.8239       | 0.8248    | 0.6990  |
| 0.6269        | 5.0   | 3500 | 0.5446          | 0.8796      | 0.8783 | 0.8845       | 0.8802    | 0.5446  |
| 0.4852        | 6.0   | 4200 | 0.4860          | 0.8862      | 0.8847 | 0.8901       | 0.8862    | 0.4860  |
| 0.4124        | 7.0   | 4900 | 0.4538          | 0.8892      | 0.8876 | 0.8925       | 0.8896    | 0.4538  |
| 0.3602        | 8.0   | 5600 | 0.4392          | 0.89        | 0.8886 | 0.8925       | 0.8906    | 0.4392  |
| 0.3355        | 9.0   | 6300 | 0.4373          | 0.8912      | 0.8898 | 0.8934       | 0.8919    | 0.4373  |
| 0.3147        | 10.0  | 7000 | 0.4353          | 0.8946      | 0.8931 | 0.8965       | 0.8952    | 0.4353  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1