
<!-- 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy", "f1"], "model-index": [{"name": "climate_text_classification_mini_model", "results": []}]}
transformers pytorch distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

climate\_text\_classification\_mini\_model
==========================================


This model is a fine-tuned version of distilbert-base-uncased on the 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



### Framework versions


* Transformers 4.26.1
* Pytorch 1.7.0a0
* Datasets 2.9.0
* Tokenizers 0.13.2



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.7.0a0
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.7.0a0
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.26.1
* Pytorch 1.7.0a0
* Datasets 2.9.0
* Tokenizers 0.13.2