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# distilbert-go-emotions

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the go_emotions dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0907
- Accuracy: 0.4287
- Precision: 0.4504
- Recall: 0.5003
- F1: 0.4702

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 340  | 0.1102          | 0.4125   | 0.2946    | 0.2139 | 0.2014 |
| 0.1347        | 2.0   | 680  | 0.0890          | 0.3900   | 0.4252    | 0.4627 | 0.4262 |
| 0.1347        | 3.0   | 1020 | 0.0860          | 0.4097   | 0.4344    | 0.4992 | 0.4578 |
| 0.0771        | 4.0   | 1360 | 0.0864          | 0.4298   | 0.4561    | 0.4974 | 0.4701 |
| 0.0771        | 5.0   | 1700 | 0.0891          | 0.4266   | 0.4522    | 0.4992 | 0.4703 |
| 0.0617        | 6.0   | 2040 | 0.0907          | 0.4287   | 0.4504    | 0.5003 | 0.4702 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["go_emotions"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "distilbert-go-emotions", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "go_emotions", "type": "go_emotions", "args": "simplified"}, "metrics": [{"type": "accuracy", "value": 0.42867674161444896, "name": "Accuracy"}, {"type": "precision", "value": 0.4503794622630937, "name": "Precision"}, {"type": "recall", "value": 0.5002719498073401, "name": "Recall"}, {"type": "f1", "value": 0.47024637118703766, "name": "F1"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:go_emotions license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-go_emotions #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

distilbert-go-emotions
======================


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


* Loss: 0.0907
* Accuracy: 0.4287
* Precision: 0.4504
* Recall: 0.5003
* F1: 0.4702


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: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-go_emotions #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-go_emotions #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1