transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:go_emotions license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- go_emotions
license: apache-2.0
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
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
---

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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
