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# BT5153-kaggle-sentiment-model-3000-samples

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: 0.6160
- Accuracy: 0.9270
- F1: 0.9288

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.2851        | 1.0   | 625  | 0.2058          | 0.9216   | 0.9231 |
| 0.1735        | 2.0   | 1250 | 0.2257          | 0.9244   | 0.9258 |
| 0.121         | 3.0   | 1875 | 0.2907          | 0.9232   | 0.9251 |
| 0.0525        | 4.0   | 2500 | 0.3607          | 0.9194   | 0.9219 |
| 0.0381        | 5.0   | 3125 | 0.4109          | 0.9216   | 0.9233 |
| 0.0257        | 6.0   | 3750 | 0.4142          | 0.9232   | 0.9244 |
| 0.0192        | 7.0   | 4375 | 0.4321          | 0.9230   | 0.9233 |
| 0.0126        | 8.0   | 5000 | 0.4745          | 0.9250   | 0.9278 |
| 0.01          | 9.0   | 5625 | 0.5053          | 0.9240   | 0.9246 |
| 0.0091        | 10.0  | 6250 | 0.5256          | 0.9240   | 0.9267 |
| 0.0062        | 11.0  | 6875 | 0.5798          | 0.9246   | 0.9255 |
| 0.0033        | 12.0  | 7500 | 0.5935          | 0.9242   | 0.9262 |
| 0.0019        | 13.0  | 8125 | 0.5891          | 0.9286   | 0.9303 |
| 0.0018        | 14.0  | 8750 | 0.6176          | 0.9266   | 0.9287 |
| 0.0001        | 15.0  | 9375 | 0.6160          | 0.9270   | 0.9288 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "BT5153-kaggle-sentiment-model-3000-samples", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

BT5153-kaggle-sentiment-model-3000-samples
==========================================


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: 0.6160
* Accuracy: 0.9270
* F1: 0.9288


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2