metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: augmented_model_one_no_decay
results: []
augmented_model_one_no_decay
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1143
- Accuracy: 0.5579
- F1: 0.5593
- Precision: 0.5630
- Recall: 0.5577
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: 3e-06
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7227 | 0.2088 | 500 | 0.7164 | 0.7085 | 0.6956 | 0.7019 | 0.6986 |
| 0.669 | 0.4175 | 1000 | 0.7047 | 0.7168 | 0.7060 | 0.7126 | 0.7080 |
| 0.6417 | 0.6263 | 1500 | 0.7017 | 0.7146 | 0.7066 | 0.7115 | 0.7077 |
| 0.6274 | 0.8351 | 2000 | 0.6977 | 0.7220 | 0.7124 | 0.7172 | 0.7139 |
| 0.6082 | 1.0438 | 2500 | 0.6994 | 0.7212 | 0.7134 | 0.7167 | 0.7142 |
| 0.5766 | 1.2526 | 3000 | 0.7056 | 0.7168 | 0.7077 | 0.7113 | 0.7090 |
| 0.5789 | 1.4614 | 3500 | 0.7004 | 0.7220 | 0.7149 | 0.7185 | 0.7155 |
| 0.578 | 1.6701 | 4000 | 0.7030 | 0.7247 | 0.7151 | 0.7191 | 0.7165 |
| 0.5743 | 1.8789 | 4500 | 0.7008 | 0.7233 | 0.7144 | 0.7174 | 0.7156 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1