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README.md
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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: tashrifmahmud/sentiment_analysis_model
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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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- precision
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- recall
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- f1
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model-index:
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- name: sentiment_analysis_model_v2
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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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# sentiment_analysis_model_v2
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This model is a fine-tuned version of [tashrifmahmud/sentiment_analysis_model](https://huggingface.co/tashrifmahmud/sentiment_analysis_model) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4342
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- Accuracy: 0.8443
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- Precision: 0.8404
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- Recall: 0.8499
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- F1: 0.8451
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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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- 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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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.365 | 1.0 | 534 | 0.3682 | 0.8396 | 0.8267 | 0.8593 | 0.8427 |
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| 0.2804 | 2.0 | 1068 | 0.3892 | 0.8452 | 0.8525 | 0.8349 | 0.8436 |
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| 0.2301 | 3.0 | 1602 | 0.4342 | 0.8443 | 0.8404 | 0.8499 | 0.8451 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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model.safetensors
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