transformers pytorch tensorboard hybridbert text-classification generated_from_trainer dataset:emotion model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- emotion
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: add-bert-emotion_24
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: emotion
      type: emotion
      config: split
      split: validation
      args: split
    metrics:
    - type: accuracy
      value: 0.359
      name: Accuracy
---

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# add-bert-emotion_24

This model is a fine-tuned version of [gokuls/add_bert_12_layer_model_complete_training_new](https://huggingface.co/gokuls/add_bert_12_layer_model_complete_training_new) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5744
- Accuracy: 0.8053

## 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: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6013        | 1.0   | 250  | 1.5840          | 0.3435   |
| 1.5884        | 2.0   | 500  | 1.5993          | 0.275    |
| 1.5783        | 3.0   | 750  | 1.5744          | 0.359    |
| 1.5814        | 4.0   | 1000 | 1.5805          | 0.3345   |
| 1.5804        | 5.0   | 1250 | 1.5820          | 0.352    |
| 1.5762        | 6.0   | 1500 | 1.5846          | 0.352    |
| 1.5781        | 7.0   | 1750 | 1.5829          | 0.352    |
| 1.5759        | 8.0   | 2000 | 1.5813          | 0.352    |
| 1.5741        | 9.0   | 2250 | 1.5835          | 0.33     |
| 1.573         | 10.0  | 2500 | 1.5795          | 0.334    |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
