End of training
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README.md
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---
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license: apache-2.0
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base_model: bert-base-multilingual-cased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: esg-classification_bert_all_data_0509
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# esg-classification_bert_all_data_0509
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1536
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- Accuracy: 0.9643
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 69 | 1.4243 | 0.6245 |
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| No log | 2.0 | 138 | 0.6974 | 0.7995 |
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| No log | 3.0 | 207 | 0.3928 | 0.8965 |
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| No log | 4.0 | 276 | 0.2440 | 0.9441 |
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| No log | 5.0 | 345 | 0.1760 | 0.9606 |
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| No log | 6.0 | 414 | 0.1536 | 0.9643 |
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### Framework versions
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- Transformers 4.33.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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