---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_Them_all
  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_Them_all

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: 0.0906
- Precision: 0.5194
- Recall: 0.5282
- F1: 0.5238
- Accuracy: 0.9716

## 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: 2e-05
- 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 251  | 0.0860          | 0.5923    | 0.3898 | 0.4702 | 0.9681   |
| 0.079         | 2.0   | 502  | 0.0782          | 0.5342    | 0.5508 | 0.5424 | 0.9723   |
| 0.079         | 3.0   | 753  | 0.0854          | 0.5234    | 0.5367 | 0.5300 | 0.9711   |
| 0.0347        | 4.0   | 1004 | 0.0906          | 0.5194    | 0.5282 | 0.5238 | 0.9716   |


### Framework versions

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