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# distilbert_imdb_genre_classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0196
- Precision: 0.4254
- Recall: 0.4432
- F1 Score: 0.4191
- Jaccard Score: 0.2966
- Average Precision Score: 0.4831
- Percentage Examples At Least 1 True: 0.8845

## 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: 5e-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 Score | Jaccard Score | Average Precision Score | Percentage Examples At Least 1 True |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:-------------:|:-----------------------:|:-----------------------------------:|
| 0.0231        | 1.0   | 1500 | 0.0214          | 0.3601    | 0.4090 | 0.3601   | 0.2523        | 0.4326                  | 0.8638                              |
| 0.0196        | 2.0   | 3000 | 0.0198          | 0.4174    | 0.4367 | 0.4064   | 0.2864        | 0.4743                  | 0.8842                              |
| 0.0172        | 3.0   | 4500 | 0.0196          | 0.4216    | 0.4418 | 0.4155   | 0.2939        | 0.4822                  | 0.887                               |
| 0.016         | 4.0   | 6000 | 0.0196          | 0.4254    | 0.4432 | 0.4191   | 0.2966        | 0.4831                  | 0.8845                              |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall"], "model-index": [{"name": "distilbert_imdb_genre_classifier", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert\_imdb\_genre\_classifier
===================================


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


* Loss: 0.0196
* Precision: 0.4254
* Recall: 0.4432
* F1 Score: 0.4191
* Jaccard Score: 0.2966
* Average Precision Score: 0.4831
* Percentage Examples At Least 1 True: 0.8845


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: 5e-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



### Framework versions


* Transformers 4.26.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 ### Framework versions


* Transformers 4.26.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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 ### Framework versions


* Transformers 4.26.1
* Pytorch 2.0.0+cu118
* Tokenizers 0.13.3