metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_model
results: []
my_model
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1133
- Precision: 0.8967
- Recall: 0.9086
- F1: 0.9026
- Accuracy: 0.9308
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1943 | 1.0 | 2241 | 0.1610 | 0.8577 | 0.8640 | 0.8608 | 0.9014 |
| 0.1341 | 2.0 | 4482 | 0.1204 | 0.8890 | 0.9014 | 0.8951 | 0.9259 |
| 0.1095 | 3.0 | 6723 | 0.1133 | 0.8967 | 0.9086 | 0.9026 | 0.9308 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1