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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: samchain/econo-sentence-v2 |
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tags: |
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- generated_from_trainer |
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- finance |
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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: EconoSentiment |
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results: [] |
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datasets: |
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- FinanceMTEB/financial_phrasebank |
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language: |
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- en |
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pipeline_tag: text-classification |
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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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# EconoSentiment |
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This model is a fine-tuned version of [samchain/econo-sentence-v2](https://huggingface.co/samchain/econo-sentence-v2) on the Financial Phrase Bank dataset from FinanceMTEB. |
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The full model is trained using a small learning rate isntead of freezing the encoder. Hence, you should not use the encoder of this model for a task other than sentiment analysis. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1293 |
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- Accuracy: 0.962 |
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- F1: 0.9619 |
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- Precision: 0.9619 |
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- Recall: 0.962 |
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## Model description |
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The base model is a sentence-transformers model built from [EconoBert](https://huggingface.co/samchain/EconoBert). |
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## Intended uses & limitations |
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This model is trained to provide a useful tool for sentiment analysis in finance. |
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## Training and evaluation data |
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The dataset is directly downloaded from the huggingface repo of the FinanceMTEB. The preprocessing consisted of tokenizing to a fixed sequence length of 512 tokens. |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 2 |
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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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| 0.5992 | 1.0 | 158 | 0.4854 | 0.805 | 0.7692 | 0.8108 | 0.805 | |
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| 0.0985 | 2.0 | 316 | 0.1293 | 0.962 | 0.9619 | 0.9619 | 0.962 | |
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### Framework versions |
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- Transformers 4.50.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
