transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:emotion license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
- precision
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased_emotion_ft_0520
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.921
      name: Accuracy
    - type: f1
      value: 0.9210292348449035
      name: F1
    - type: precision
      value: 0.8947253235549543
      name: Precision
---

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# distilbert-base-uncased_emotion_ft_0520

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2557
- Accuracy: 0.921
- F1: 0.9210
- Precision: 0.8947

## 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: 256
- eval_batch_size: 256
- 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 | Accuracy | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 63   | 0.9006          | 0.7055   | 0.6410 | 0.4988    |
| No log        | 2.0   | 126  | 0.4166          | 0.8805   | 0.8729 | 0.8886    |
| No log        | 3.0   | 189  | 0.2844          | 0.9175   | 0.9167 | 0.8987    |
| 0.6518        | 4.0   | 252  | 0.2557          | 0.921    | 0.9210 | 0.8947    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
