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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: sentence-transformers/all-mpnet-base-v2 |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: all-mpnet-base-v2-sentiment-twitter |
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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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# all-mpnet-base-v2-sentiment-twitter |
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This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6390 |
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- Accuracy: 0.7169 |
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- F1: 0.7156 |
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- Precision: 0.7224 |
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- Recall: 0.7169 |
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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: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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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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| 0.714 | 0.1754 | 500 | 0.7064 | 0.699 | 0.6941 | 0.7038 | 0.699 | |
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| 0.6676 | 0.3508 | 1000 | 0.6255 | 0.7225 | 0.7260 | 0.7353 | 0.7225 | |
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| 0.6394 | 0.5261 | 1500 | 0.6229 | 0.7265 | 0.7287 | 0.7371 | 0.7265 | |
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| 0.6408 | 0.7015 | 2000 | 0.6101 | 0.73 | 0.7250 | 0.7330 | 0.73 | |
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| 0.6069 | 0.8769 | 2500 | 0.5878 | 0.749 | 0.7500 | 0.7516 | 0.749 | |
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| 0.4633 | 1.0523 | 3000 | 0.6304 | 0.7485 | 0.7482 | 0.7548 | 0.7485 | |
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| 0.5003 | 1.2276 | 3500 | 0.6054 | 0.747 | 0.7486 | 0.7518 | 0.747 | |
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| 0.4594 | 1.4030 | 4000 | 0.6955 | 0.7205 | 0.7146 | 0.7315 | 0.7205 | |
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| 0.4721 | 1.5784 | 4500 | 0.5965 | 0.7555 | 0.7553 | 0.7565 | 0.7555 | |
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| 0.4601 | 1.7538 | 5000 | 0.6504 | 0.7385 | 0.7389 | 0.7436 | 0.7385 | |
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| 0.4762 | 1.9291 | 5500 | 0.5998 | 0.757 | 0.7564 | 0.7573 | 0.757 | |
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| 0.4 | 2.1045 | 6000 | 0.6574 | 0.7535 | 0.7533 | 0.7538 | 0.7535 | |
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| 0.4021 | 2.2799 | 6500 | 0.6714 | 0.75 | 0.7498 | 0.7505 | 0.75 | |
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| 0.3477 | 2.4553 | 7000 | 0.6803 | 0.7495 | 0.7495 | 0.7496 | 0.7495 | |
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| 0.3616 | 2.6307 | 7500 | 0.6996 | 0.745 | 0.7448 | 0.7459 | 0.745 | |
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| 0.3692 | 2.8060 | 8000 | 0.6872 | 0.748 | 0.7484 | 0.7502 | 0.748 | |
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| 0.3549 | 2.9814 | 8500 | 0.6903 | 0.749 | 0.7487 | 0.7499 | 0.749 | |
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### Framework versions |
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- Transformers 4.55.4 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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