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Training complete

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README.md ADDED
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+ ---
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+ library_name: transformers
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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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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: finbert_finetuned
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+ results: []
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+ ---
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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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+
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+ # finbert_finetuned
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+
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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: 0.2258
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+ - Precision: 0.5938
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+ - Recall: 0.6849
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+ - F1: 0.6361
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+ - Accuracy: 0.9243
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.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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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 125 | 0.2695 | 0.5179 | 0.6058 | 0.5584 | 0.9156 |
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+ | No log | 2.0 | 250 | 0.2311 | 0.5785 | 0.6686 | 0.6203 | 0.9246 |
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+ | No log | 3.0 | 375 | 0.2258 | 0.5938 | 0.6849 | 0.6361 | 0.9243 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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