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--- |
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base_model: ProsusAI/finbert |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: finbert_Synonym-wordnet |
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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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# finbert_Synonym-wordnet |
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This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2734 |
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- Accuracy: 0.9236 |
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- F1: 0.9232 |
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- Precision: 0.9236 |
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- Recall: 0.9236 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.7941 | 1.0 | 91 | 0.7038 | 0.7051 | 0.6964 | 0.7046 | 0.7051 | |
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| 0.3785 | 2.0 | 182 | 0.2841 | 0.8939 | 0.8940 | 0.8942 | 0.8939 | |
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| 0.213 | 3.0 | 273 | 0.2432 | 0.9080 | 0.9082 | 0.9106 | 0.9080 | |
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| 0.1268 | 4.0 | 364 | 0.3080 | 0.8924 | 0.8927 | 0.8956 | 0.8924 | |
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| 0.0851 | 5.0 | 455 | 0.2941 | 0.9173 | 0.9166 | 0.9183 | 0.9173 | |
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| 0.0797 | 6.0 | 546 | 0.2734 | 0.9236 | 0.9232 | 0.9236 | 0.9236 | |
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| 0.0651 | 7.0 | 637 | 0.3518 | 0.8970 | 0.8975 | 0.9029 | 0.8970 | |
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| 0.0779 | 8.0 | 728 | 0.4189 | 0.8939 | 0.8942 | 0.9016 | 0.8939 | |
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| 0.0923 | 9.0 | 819 | 0.3289 | 0.9126 | 0.9131 | 0.9152 | 0.9126 | |
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| 0.087 | 10.0 | 910 | 0.3797 | 0.9048 | 0.9047 | 0.9075 | 0.9048 | |
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| 0.0527 | 11.0 | 1001 | 0.3492 | 0.9048 | 0.9050 | 0.9058 | 0.9048 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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