
### finetuned-distilbert-adult-content-catgorization

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the adult_content dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0065
- F1_score(weighted): 0.90
### Model description
 More information needed
### Intended uses & limitations
More information needed
### Training and evaluation data
The model was trained on some subset of the adult_content dataset and it was validated on the remaining subset of the data
### Training procedure
More information needed
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-5
- train_batch_size: 5
- eval_batch_size: 5
- seed: 17
- optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0
- num_epochs: 2
### Training results
| Training Loss | Epoch |  Validation Loss | f1 score   |
|:-------------:|:-----:|:---------------: |:------:|
| 0.1414        | 1.0   | 0.4585           | 0.9058 |
| 0.1410        | 2.0   | 0.4584           | 0.9058 |

{"license": "other", "tags": ["generated_from_trainer"], "model-index": [{"name": "finetuned-distilbert-adult-content-detection", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:other autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #has_space #region-us 

### finetuned-distilbert-adult-content-catgorization


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


* Loss: 0.0065
* F1\_score(weighted): 0.90


### Model description


More information needed


### Intended uses & limitations


More information needed


### Training and evaluation data


The model was trained on some subset of the adult\_content dataset and it was validated on the remaining subset of the data


### Training procedure


More information needed


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-5
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 17
* optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 0
* num\_epochs: 2


### Training results




### finetuned-distilbert-adult-content-catgorization


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


* Loss: 0.0065
* F1\_score(weighted): 0.90 ### Model description


More information needed ### Intended uses & limitations


More information needed ### Training and evaluation data


The model was trained on some subset of the adult\_content dataset and it was validated on the remaining subset of the data ### Training procedure


More information needed ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-5
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 17
* optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 0
* num\_epochs: 2 ### Training results
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### finetuned-distilbert-adult-content-catgorization


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


* Loss: 0.0065
* F1\_score(weighted): 0.90 ### Model description


More information needed ### Intended uses & limitations


More information needed ### Training and evaluation data


The model was trained on some subset of the adult\_content dataset and it was validated on the remaining subset of the data ### Training procedure


More information needed ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-5
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 17
* optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 0
* num\_epochs: 2 ### Training results
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #has_space #region-us 
### finetuned-distilbert-adult-content-catgorization


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


* Loss: 0.0065
* F1\_score(weighted): 0.90### Model description


More information needed### Intended uses & limitations


More information needed### Training and evaluation data


The model was trained on some subset of the adult\_content dataset and it was validated on the remaining subset of the data### Training procedure


More information needed### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-5
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 17
* optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 0
* num\_epochs: 2### Training results