metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: roberta-large
model-index:
- name: roberta-large-go-emotions
results: []
roberta-large-go-emotions
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0811
- Accuracy: 0.4525
- Precision: 0.5113
- Recall: 0.5202
- F1: 0.5057
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 679 | 0.0936 | 0.4233 | 0.4251 | 0.4021 | 0.3955 |
| 0.1094 | 2.0 | 1358 | 0.0826 | 0.4432 | 0.4828 | 0.4888 | 0.4747 |
| 0.1094 | 3.0 | 2037 | 0.0811 | 0.4525 | 0.5113 | 0.5202 | 0.5057 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.1