---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: esg-classification_bert_all_data_0509
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# esg-classification_bert_all_data_0509

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1536
- Accuracy: 0.9643

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 69   | 1.4243          | 0.6245   |
| No log        | 2.0   | 138  | 0.6974          | 0.7995   |
| No log        | 3.0   | 207  | 0.3928          | 0.8965   |
| No log        | 4.0   | 276  | 0.2440          | 0.9441   |
| No log        | 5.0   | 345  | 0.1760          | 0.9606   |
| No log        | 6.0   | 414  | 0.1536          | 0.9643   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3