Edit model card

esg-classification_bert_all_data_0509_other_v1

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6887
  • Accuracy: 0.8153

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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 63 1.7731 0.4217
No log 2.0 126 1.0752 0.7068
No log 3.0 189 0.8234 0.7631
No log 4.0 252 0.7167 0.8112
No log 5.0 315 0.6887 0.8153

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
7
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for dsmsb/esg-classification_bert_all_data_0509_other_v1

Finetuned
(511)
this model