transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:go_emotions license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- go_emotions
license: mit
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: roberta-large-go-emotions-2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: go_emotions
      type: multilabel_classification
      config: simplified
      split: test
      args: simplified
    metrics:
    - type: f1
      value: 0.518
      name: F1
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: go_emotions
      type: multilabel_classification
      config: simplified
      split: validation
      args: simplified
    metrics:
    - type: f1
      value: 0.5203
      name: F1
---

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# roberta-large-go-emotions-2

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset. It achieves the following results on the test set (with a threshold of 0.15):

- Accuracy: 0.44020
- Precision: 0.5041
- Recall: 0.5461
- F1: 0.5180

## 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: 9

### Training results

| Training Loss | Epoch | Validation Loss | Accuracy | Precision | Recall | F1     |
| ------------- | ----- | --------------- | -------- | --------- | ------ | ------ |
| No log        | 1.0   | 0.0889          | 0.4043   | 0.4807    | 0.4568 | 0.4446 |
| 0.1062        | 2.0   | 0.0828          | 0.4113   | 0.4608    | 0.5363 | 0.4868 |
| 0.1062        | 3.0   | 0.0813          | 0.4201   | 0.5198    | 0.5612 | 0.5227 |
| No log        | 4.0   | 0.0862          | 0.4292   | 0.5012    | 0.5558 | 0.5208 |
| 0.0597        | 5.0   | 0.0924          | 0.4329   | 0.5164    | 0.5362 | 0.5151 |
| 0.0597        | 6.0   | 0.0956          | 0.4445   | 0.5241    | 0.5328 | 0.5161 |
| No log        | 7.0   | 0.0962          | 0.4648   | 0.5138    | 0.5277 | 0.5151 |
| 0.0458        | 8.0   | 0.0962          | 0.4462   | 0.5257    | 0.5270 | 0.5203 |
| 0.0458        | 9.0   | 0.1029          | 0.4432   | 0.5076    | 0.5249 | 0.5111 |

### Framework versions

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