metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: my_fancy_model
results: []
my_fancy_model
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: 0.6695
- Accuracy: 0.65
- Recall: 0.5
- Precision: 0.325
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision |
|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 0.7025 | 0.65 | 0.5 | 0.325 |
| No log | 2.0 | 14 | 0.6968 | 0.65 | 0.5 | 0.325 |
| No log | 3.0 | 21 | 0.8017 | 0.65 | 0.5 | 0.325 |
| No log | 4.0 | 28 | 0.6836 | 0.65 | 0.5 | 0.325 |
| No log | 5.0 | 35 | 0.6695 | 0.65 | 0.5 | 0.325 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2