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all-mpnet-base-v2-sentiment-twitter

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metadata
library_name: transformers
license: apache-2.0
base_model: sentence-transformers/all-mpnet-base-v2
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: all-mpnet-base-v2-sentiment-twitter
    results: []

all-mpnet-base-v2-sentiment-twitter

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6390
  • Accuracy: 0.7169
  • F1: 0.7156
  • Precision: 0.7224
  • Recall: 0.7169

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.714 0.1754 500 0.7064 0.699 0.6941 0.7038 0.699
0.6676 0.3508 1000 0.6255 0.7225 0.7260 0.7353 0.7225
0.6394 0.5261 1500 0.6229 0.7265 0.7287 0.7371 0.7265
0.6408 0.7015 2000 0.6101 0.73 0.7250 0.7330 0.73
0.6069 0.8769 2500 0.5878 0.749 0.7500 0.7516 0.749
0.4633 1.0523 3000 0.6304 0.7485 0.7482 0.7548 0.7485
0.5003 1.2276 3500 0.6054 0.747 0.7486 0.7518 0.747
0.4594 1.4030 4000 0.6955 0.7205 0.7146 0.7315 0.7205
0.4721 1.5784 4500 0.5965 0.7555 0.7553 0.7565 0.7555
0.4601 1.7538 5000 0.6504 0.7385 0.7389 0.7436 0.7385
0.4762 1.9291 5500 0.5998 0.757 0.7564 0.7573 0.757
0.4 2.1045 6000 0.6574 0.7535 0.7533 0.7538 0.7535
0.4021 2.2799 6500 0.6714 0.75 0.7498 0.7505 0.75
0.3477 2.4553 7000 0.6803 0.7495 0.7495 0.7496 0.7495
0.3616 2.6307 7500 0.6996 0.745 0.7448 0.7459 0.745
0.3692 2.8060 8000 0.6872 0.748 0.7484 0.7502 0.748
0.3549 2.9814 8500 0.6903 0.749 0.7487 0.7499 0.749

Framework versions

  • Transformers 4.55.4
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.21.4