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# distilbert_reviews_with_language_drift

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ecommerce_reviews_with_language_drift dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4970
- Accuracy: 0.818
- F1: 0.8167

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.593         | 1.0   | 500  | 0.4723          | 0.799    | 0.7976 |
| 0.3714        | 2.0   | 1000 | 0.4679          | 0.818    | 0.8177 |
| 0.2652        | 3.0   | 1500 | 0.4970          | 0.818    | 0.8167 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ecommerce_reviews_with_language_drift"], "metrics": ["accuracy", "f1"], "widget": [{"text": "Poor quality of fabric and ridiculously tight at chest. It's way too short.", "example_title": "Negative"}, {"text": "One worked perfectly, but the other one has a slight leak and we end up with water underneath the filter.", "example_title": "Neutral"}, {"text": "I liked the price most! Nothing to dislike here!", "example_title": "Positive"}], "model-index": [{"name": "distilbert_reviews_with_language_drift", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "ecommerce_reviews_with_language_drift", "type": "ecommerce_reviews_with_language_drift", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.818, "name": "Accuracy"}, {"type": "f1", "value": 0.8167126877417763, "name": "F1"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:ecommerce_reviews_with_language_drift license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-ecommerce_reviews_with_language_drift #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert\_reviews\_with\_language\_drift
==========================================


This model is a fine-tuned version of distilbert-base-uncased on the ecommerce\_reviews\_with\_language\_drift dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4970
* Accuracy: 0.818
* F1: 0.8167


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: 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: 3


### Training results



### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 3 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-ecommerce_reviews_with_language_drift #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: 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: 3 ### Training results ### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-ecommerce_reviews_with_language_drift #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: 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: 3### Training results### Framework versions


* Transformers 4.19.2
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1