metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: climate-fact-checker
results: []
pipeline_tag: text-classification
language:
- en
library_name: transformers
climate-fact-checker
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2740
- Accuracy: 0.6975
- F1: 0.6768
- Precision: 0.6819
- Recall: 0.6975
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 | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 384 | 0.3141 | 0.6836 | 0.6113 | 0.6934 | 0.6836 |
| 0.3433 | 2.0 | 768 | 0.2599 | 0.7148 | 0.6995 | 0.7028 | 0.7148 |
| 0.2239 | 3.0 | 1152 | 0.2601 | 0.7018 | 0.7032 | 0.7067 | 0.7018 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1