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umarvinci/distilbert-base-uncased-lora-financial-sentiment-analysis

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README.md ADDED
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+ ---
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+ base_model: distilbert-base-uncased
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+ datasets:
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+ - financial_phrasebank
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+ library_name: peft
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+ license: apache-2.0
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+ metrics:
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+ - accuracy
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert-base-uncased-lora-financial-sentiment-analysis
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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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+ # distilbert-base-uncased-lora-financial-sentiment-analysis
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0637
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+ - Accuracy: {'accuracy': 0.9779735682819384}
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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: 0.001
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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: 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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|
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+ | 0.3143 | 1.0 | 510 | 0.0637 | {'accuracy': 0.9779735682819384} |
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+ | 0.1253 | 2.0 | 1020 | 0.0722 | {'accuracy': 0.973568281938326} |
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+ | 0.0574 | 3.0 | 1530 | 0.0806 | {'accuracy': 0.973568281938326} |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.42.1
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+ - Pytorch 2.0.1+cpu
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "init_lora_weights": true,
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+ "peft_type": "LORA",
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+ "q_lin"
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+ "use_rslora": false
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+ }
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