license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-finetuned-FinanceNews-distilbert
results: []
my-finetuned-FinanceNews-distilbert
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3800
Accuracy: 0.8557
F1: 0.8547
Precision: 0.8548
Recall: 0.8557
Classification Report: precision recall f1-score support
Class 0 0.87 0.90 0.88 87 Class 1 0.87 0.90 0.88 268 Class 2 0.83 0.76 0.79 151
accuracy 0.86 506 macro avg 0.85 0.85 0.85 506
weighted avg 0.85 0.86 0.85 506
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Classification Report |
|---|---|---|---|---|---|---|---|---|
| 0.7555 | 1.0 | 72 | 0.4573 | 0.8241 | 0.8235 | 0.8232 | 0.8241 | precision recall f1-score support |
Class 0 0.83 0.84 0.83 87
Class 1 0.85 0.87 0.86 268
Class 2 0.78 0.74 0.76 151
accuracy 0.82 506
macro avg 0.82 0.82 0.82 506 weighted avg 0.82 0.82 0.82 506 | | 0.4201 | 2.0 | 144 | 0.3800 | 0.8557 | 0.8547 | 0.8548 | 0.8557 | precision recall f1-score support
Class 0 0.87 0.90 0.88 87
Class 1 0.87 0.90 0.88 268
Class 2 0.83 0.76 0.79 151
accuracy 0.86 506
macro avg 0.85 0.85 0.85 506 weighted avg 0.85 0.86 0.85 506 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.2.2
- Datasets 2.20.0
- Tokenizers 0.19.1