metadata
license: mit
tags:
- generated_from_trainer
datasets:
- go_emotions
metrics:
- f1
- accuracy
model-index:
- name: pretrained_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: go_emotions
type: go_emotions
config: simplified
split: validation
args: simplified
metrics:
- name: F1
type: f1
value: 0.572835583796664
- name: Accuracy
type: accuracy
value: 0.45466273497972726
pretrained_model
This model is a fine-tuned version of roberta-large on the go_emotions dataset. It achieves the following results on the evaluation set:
- Loss: 0.1240
- F1: 0.5728
- Roc Auc: 0.7737
- Accuracy: 0.4547
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: 42
- 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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.1205 | 1.0 | 679 | 0.0865 | 0.5632 | 0.7347 | 0.4458 |
| 0.0859 | 2.0 | 1358 | 0.0829 | 0.5717 | 0.7378 | 0.4521 |
| 0.0727 | 3.0 | 2037 | 0.0827 | 0.5897 | 0.7523 | 0.4753 |
| 0.0629 | 4.0 | 2716 | 0.0857 | 0.5808 | 0.7535 | 0.4652 |
| 0.0568 | 5.0 | 3395 | 0.0904 | 0.5868 | 0.7616 | 0.4821 |
| 0.0423 | 6.0 | 4074 | 0.0989 | 0.5806 | 0.7682 | 0.4724 |
| 0.0344 | 7.0 | 4753 | 0.1079 | 0.5736 | 0.7657 | 0.4650 |
| 0.0296 | 8.0 | 5432 | 0.1158 | 0.5637 | 0.7649 | 0.4504 |
| 0.0206 | 9.0 | 6111 | 0.1200 | 0.5674 | 0.7689 | 0.4486 |
| 0.0177 | 10.0 | 6790 | 0.1240 | 0.5728 | 0.7737 | 0.4547 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2