metadata
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- generator
metrics:
- accuracy
- f1
model-index:
- name: test_emotion_detection_gersti
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: generator
type: generator
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5371057513914657
- name: F1
type: f1
value: 0.14268320711165708
test_emotion_detection_gersti
This model is a fine-tuned version of xlm-roberta-base on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.6884
- Accuracy: 0.5371
- F1: 0.1427
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3