metadata

license: apache-2.0
base_model: climatebert/distilroberta-base-climate-f
tags:
  - generated_from_trainer
model-index:
  - name: SECTOR-multilabel-climatebert
    results: []

SECTOR-multilabel-climatebert

This model is a fine-tuned version of climatebert/distilroberta-base-climate-f on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6028
Precision-micro: 0.6395
Precision-samples: 0.7543
Precision-weighted: 0.6475
Recall-micro: 0.7762
Recall-samples: 0.8583
Recall-weighted: 0.7762
F1-micro: 0.7012
F1-samples: 0.7655
F1-weighted: 0.7041

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: 9.07e-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: cosine
lr_scheduler_warmup_steps: 300
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision-micro	Precision-samples	Precision-weighted	Recall-micro	Recall-samples	Recall-weighted	F1-micro	F1-samples	F1-weighted
0.6978	1.0	633	0.5968	0.3948	0.5274	0.4982	0.7873	0.8675	0.7873	0.5259	0.5996	0.5793
0.485	2.0	1266	0.5255	0.5089	0.6365	0.5469	0.7984	0.8749	0.7984	0.6216	0.6907	0.6384
0.3657	3.0	1899	0.5248	0.4984	0.6617	0.5397	0.8141	0.8769	0.8141	0.6183	0.7066	0.6393
0.2585	4.0	2532	0.5457	0.5807	0.7148	0.5992	0.8007	0.8752	0.8007	0.6732	0.7449	0.6813
0.1841	5.0	3165	0.5551	0.6016	0.7426	0.6192	0.7937	0.8677	0.7937	0.6844	0.7590	0.6917
0.1359	6.0	3798	0.5913	0.6349	0.7506	0.6449	0.7844	0.8676	0.7844	0.7018	0.7667	0.7057
0.1133	7.0	4431	0.6028	0.6395	0.7543	0.6475	0.7762	0.8583	0.7762	0.7012	0.7655	0.7041

Framework versions

Transformers 4.38.1
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2