metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-finetuned-go-emotions_dataset
results: []
distilbert-finetuned-go-emotions_dataset
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5221
- Accuracy: 0.5844
- F1: 0.5241
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 262 | 1.9841 | 0.4993 | 0.3718 |
| 2.1649 | 2.0 | 524 | 1.6903 | 0.5508 | 0.4546 |
| 2.1649 | 3.0 | 786 | 1.5779 | 0.5732 | 0.4992 |
| 1.5746 | 4.0 | 1048 | 1.5320 | 0.5800 | 0.5114 |
| 1.5746 | 5.0 | 1310 | 1.5221 | 0.5844 | 0.5241 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1