metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
results: []
results
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1181
- Accuracy: 0.9667
- Precision: 0.9687
- Recall: 0.9667
- F1: 0.9666
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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2806 | 0.9895 | 59 | 0.2562 | 0.8833 | 0.8896 | 0.8833 | 0.8824 |
| 0.047 | 1.9958 | 119 | 0.1286 | 0.9583 | 0.9596 | 0.9583 | 0.9584 |
| 0.0946 | 2.9853 | 178 | 0.1196 | 0.9667 | 0.9672 | 0.9667 | 0.9667 |
| 0.0037 | 3.9916 | 238 | 0.1181 | 0.9667 | 0.9687 | 0.9667 | 0.9666 |
| 0.0021 | 4.9979 | 298 | 0.1189 | 0.9667 | 0.9671 | 0.9667 | 0.9666 |
| 0.0039 | 5.9874 | 357 | 0.1515 | 0.9667 | 0.9672 | 0.9667 | 0.9667 |
| 0.0013 | 6.9937 | 417 | 0.1703 | 0.9667 | 0.9667 | 0.9667 | 0.9667 |
| 0.0012 | 8.0 | 477 | 0.1703 | 0.9583 | 0.9585 | 0.9583 | 0.9583 |
| 0.0011 | 8.9895 | 536 | 0.1841 | 0.9667 | 0.9672 | 0.9667 | 0.9667 |
| 0.001 | 9.8952 | 590 | 0.1797 | 0.9667 | 0.9672 | 0.9667 | 0.9667 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1