sentiment_analytics_bert_drop_50_50

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sentiment_analytics_bert_drop_50_50

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3765

accuracy

: 0.8279

f1

: 0.8288

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 50

Training results

| Training Loss | Epoch | Step | Validation Loss |

accuracy

|

f1

| |:-------------:|:-----:|:----:|:---------------:|:------------:|:------:| | No log | 1.0 | 414 | 0.3856 | 0.8442 | 0.8413 | | 0.4544 | 2.0 | 828 | 0.3765 | 0.8279 | 0.8288 | | 0.3352 | 3.0 | 1242 | 0.4254 | 0.8419 | 0.8360 | | 0.2233 | 4.0 | 1656 | 0.5250 | 0.8326 | 0.8334 |

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1