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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- financial_phrasebank |
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metrics: |
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- recall |
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- accuracy |
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- precision |
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model-index: |
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- name: financial_sentiment_model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: financial_phrasebank |
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type: financial_phrasebank |
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args: sentences_50agree |
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metrics: |
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- name: Recall |
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type: recall |
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value: 0.8839956357328868 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8804123711340206 |
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- name: Precision |
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type: precision |
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value: 0.8604175202419276 |
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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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# financial_sentiment_model |
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This model is a fine-tuned version of [deepmind/language-perceiver](https://huggingface.co/deepmind/language-perceiver) on the financial_phrasebank dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3467 |
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- Recall: 0.8840 |
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- Accuracy: 0.8804 |
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- Precision: 0.8604 |
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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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- distributed_type: tpu |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Recall | Accuracy | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:| |
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| 0.4481 | 1.0 | 273 | 0.4035 | 0.8526 | 0.8433 | 0.7955 | |
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| 0.4069 | 2.0 | 546 | 0.4478 | 0.8683 | 0.8289 | 0.8123 | |
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| 0.2225 | 3.0 | 819 | 0.3167 | 0.8747 | 0.8680 | 0.8387 | |
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| 0.1245 | 4.0 | 1092 | 0.3467 | 0.8840 | 0.8804 | 0.8604 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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