---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_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_awesome_wnut_model

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0832
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9821

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 118  | 0.0767          | 0.0       | 0.0    | 0.0 | 0.9725   |
| No log        | 2.0   | 236  | 0.0554          | 0.0       | 0.0    | 0.0 | 0.9799   |
| No log        | 3.0   | 354  | 0.0695          | 0.0       | 0.0    | 0.0 | 0.9799   |
| No log        | 4.0   | 472  | 0.0762          | 0.0       | 0.0    | 0.0 | 0.9795   |
| 0.0497        | 5.0   | 590  | 0.0888          | 0.0       | 0.0    | 0.0 | 0.9804   |
| 0.0497        | 6.0   | 708  | 0.0820          | 0.0       | 0.0    | 0.0 | 0.9812   |
| 0.0497        | 7.0   | 826  | 0.0877          | 0.0       | 0.0    | 0.0 | 0.9814   |
| 0.0497        | 8.0   | 944  | 0.0864          | 0.0       | 0.0    | 0.0 | 0.9815   |
| 0.003         | 9.0   | 1062 | 0.0876          | 0.0       | 0.0    | 0.0 | 0.9823   |
| 0.003         | 10.0  | 1180 | 0.0832          | 0.0       | 0.0    | 0.0 | 0.9821   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1
- Datasets 2.19.0
- Tokenizers 0.19.1