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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: climate_text_classification_mini_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# climate_text_classification_mini_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [climate-tagging-labelled-datasets](https://huggingface.co/datasets/maayansharon/climate-tagging-labelled-datasets) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7516
- Precision: 0.7941
- Recall: 0.9643
- Accuracy: 0.8
- F1: {'f1': 0.8709677419354839}
## 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: 0.0002
- 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------------------------:|
| No log | 1.0 | 10 | 0.5469 | 0.875 | 0.75 | 0.75 | {'f1': 0.8076923076923077} |
| No log | 2.0 | 20 | 0.7516 | 0.7941 | 0.9643 | 0.8 | {'f1': 0.8709677419354839} |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.7.0a0
- Datasets 2.9.0
- Tokenizers 0.13.2
|