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# movie-genre-prediction_distilbert-base-uncased

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5869
- Accuracy: 0.4489

## 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: 200
- eval_batch_size: 200
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 163  | 1.6259          | 0.4358   |
| No log        | 2.0   | 326  | 1.5705          | 0.4478   |
| No log        | 3.0   | 489  | 1.5566          | 0.4527   |
| 1.6342        | 4.0   | 652  | 1.5656          | 0.4537   |
| 1.6342        | 5.0   | 815  | 1.5721          | 0.4504   |
| 1.6342        | 6.0   | 978  | 1.5825          | 0.4491   |
| 1.3404        | 7.0   | 1141 | 1.5869          | 0.4489   |


### Framework versions

- Transformers 4.24.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3

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

movie-genre-prediction\_distilbert-base-uncased
===============================================


This model is a fine-tuned version of distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.5869
* Accuracy: 0.4489


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: 200
* eval\_batch\_size: 200
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 200
* eval\_batch\_size: 200
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #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: 200
* eval\_batch\_size: 200
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 7 ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3