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# distilbert-base-uncased-finetuned-health_facts

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the health_fact dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1227
- Accuracy: 0.6285
- F1: 0.6545

## 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: 64
- eval_batch_size: 64
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.1367        | 1.0   | 154  | 0.9423          | 0.5560   | 0.6060 |
| 0.9444        | 2.0   | 308  | 0.9267          | 0.5733   | 0.6170 |
| 0.8248        | 3.0   | 462  | 0.9483          | 0.5832   | 0.6256 |
| 0.7213        | 4.0   | 616  | 1.0119          | 0.5815   | 0.6219 |
| 0.608         | 5.0   | 770  | 1.1227          | 0.6285   | 0.6545 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0
- Datasets 1.16.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["health_fact"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "distilbert-base-uncased-finetuned-health_facts", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "health_fact", "type": "health_fact", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.628500823723229, "name": "Accuracy"}, {"type": "f1", "value": 0.6544946803476833, "name": "F1"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:health_fact license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-health_fact #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased-finetuned-health\_facts
===============================================


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


* Loss: 1.1227
* Accuracy: 0.6285
* F1: 0.6545


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: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-health_fact #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-health_fact #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.0
* Datasets 1.16.1
* Tokenizers 0.10.3