metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: learn_hf_food_not_food_text_classifier-distilbert-base-uncased
results: []
learn_hf_food_not_food_text_classifier-distilbert-base-uncased
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: 0.0006
- Accuracy: 1.0
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3264 | 1.0 | 9 | 0.0895 | 0.9709 |
| 0.0372 | 2.0 | 18 | 0.0223 | 0.9964 |
| 0.0225 | 3.0 | 27 | 0.0022 | 1.0 |
| 0.0023 | 4.0 | 36 | 0.0015 | 1.0 |
| 0.0015 | 5.0 | 45 | 0.0010 | 1.0 |
| 0.0012 | 6.0 | 54 | 0.0008 | 1.0 |
| 0.0009 | 7.0 | 63 | 0.0007 | 1.0 |
| 0.0008 | 8.0 | 72 | 0.0006 | 1.0 |
| 0.0009 | 9.0 | 81 | 0.0006 | 1.0 |
| 0.0007 | 10.0 | 90 | 0.0006 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1