metadata
base_model: distilbert/distilbert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
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: 0.3829
- Accuracy: 0.9002
- F1: 0.9024
- Precision: 0.8993
- Recall: 0.9054
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: 16
- eval_batch_size: 64
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1293 | 1.0 | 4210 | 0.3084 | 0.8922 | 0.8941 | 0.8941 | 0.8941 |
| 0.0939 | 2.0 | 8420 | 0.3646 | 0.8933 | 0.9001 | 0.8604 | 0.9437 |
| 0.0981 | 3.0 | 12630 | 0.3829 | 0.9002 | 0.9024 | 0.8993 | 0.9054 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1