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# bert_emo_classifier

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3768

## Target Labels

label: a classification label, with possible values including 
- sadness : 0 
- joy : 1 
- love : 2 
- anger : 3 
- fear : 4 
- surprise : 5

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1497        | 0.25  | 500  | 0.2911          |
| 0.1221        | 0.5   | 1000 | 0.3190          |
| 0.108         | 0.75  | 1500 | 0.3343          |
| 0.1296        | 1.0   | 2000 | 0.2803          |
| 0.0611        | 1.25  | 2500 | 0.3392          |
| 0.0651        | 1.5   | 3000 | 0.3400          |
| 0.0588        | 1.75  | 3500 | 0.3733          |
| 0.0993        | 2.0   | 4000 | 0.3672          |
| 0.0385        | 2.25  | 4500 | 0.4041          |
| 0.0509        | 2.5   | 5000 | 0.3906          |
| 0.0651        | 2.75  | 5500 | 0.3809          |
| 0.0693        | 3.0   | 6000 | 0.3944          |
| 0.0471        | 3.25  | 6500 | 0.3926          |
| 0.0462        | 3.5   | 7000 | 0.3837          |
| 0.0326        | 3.75  | 7500 | 0.3752          |
| 0.0233        | 4.0   | 8000 | 0.3768          |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["emotion"], "model-index": [{"name": "bert_emo_classifier", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:emotion license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-emotion #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert\_emo\_classifier
=====================


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


* Loss: 0.3768


Target Labels
-------------


label: a classification label, with possible values including


* sadness : 0
* joy : 1
* love : 2
* anger : 3
* fear : 4
* surprise : 5


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: 8
* eval\_batch\_size: 8
* 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 4.15.0
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.15.0
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-emotion #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: 8
* eval\_batch\_size: 8
* 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 4.15.0
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #dataset-emotion #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: 8
* eval\_batch\_size: 8
* 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 4.15.0
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.10.3