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# covid_miss_information_classification2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an tweets dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0174
- Accuracy: 0.9966

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1244        | 1.0   | 1132 | 0.0497          | 0.9861   |
| 0.0587        | 2.0   | 2264 | 0.0383          | 0.9906   |
| 0.0244        | 3.0   | 3396 | 0.0213          | 0.9951   |
| 0.0046        | 4.0   | 4528 | 0.0202          | 0.9966   |
| 0.0047        | 5.0   | 5660 | 0.0174          | 0.9966   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "covid_miss_information_classification2", "results": []}]}
transformers pytorch safetensors distilbert text-classification generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

covid\_miss\_information\_classification2
=========================================


This model is a fine-tuned version of distilbert-base-uncased on an tweets dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0174
* Accuracy: 0.9966


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: 5


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #safetensors #distilbert #text-classification #generated_from_trainer #base_model-distilbert-base-uncased #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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: 5 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3