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metadata
base_model: ahmedrachid/FinancialBERT-Sentiment-Analysis
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: sentiment_pc_under_sampler
    results: []

sentiment_pc_under_sampler

This model is a fine-tuned version of ahmedrachid/FinancialBERT-Sentiment-Analysis on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5934
  • Accuracy: 0.8235
  • F1: 0.8236

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: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 0.4464 50 0.5398 0.7797 0.7809
No log 0.8929 100 0.4638 0.8203 0.8221
No log 1.3393 150 0.4749 0.8183 0.8196
No log 1.7857 200 0.4944 0.8144 0.8150
No log 2.2321 250 0.5050 0.8157 0.8158
No log 2.6786 300 0.5470 0.8085 0.8079
No log 3.125 350 0.5299 0.8196 0.8200
No log 3.5714 400 0.5651 0.8150 0.8146
No log 4.0179 450 0.5684 0.8288 0.8294
0.3419 4.4643 500 0.5934 0.8235 0.8236
0.3419 4.9107 550 0.5976 0.8203 0.8208

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1