metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-goemotion
results: []
distilbert-base-uncased-finetuned-goemotion
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: 1.4843
- Accuracy: 0.6095
- F1: 0.6046
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-06
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
1.8937 | 1.0 | 284 | 1.3231 | 0.6084 | 0.5807 |
1.1892 | 2.0 | 568 | 1.2584 | 0.6253 | 0.6102 |
0.8689 | 3.0 | 852 | 1.3251 | 0.6207 | 0.6111 |
0.5682 | 4.0 | 1136 | 1.4843 | 0.6095 | 0.6046 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1