merged_sentiments

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merged_sentiments

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: 0.4255

accuracy

: 0.8453

f1

: 0.8411

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 | 0.3765 | 0.8523 | 0.8500 | | 0.4454 | 2.0 | 828 | 0.3769 | 0.8314 | 0.8323 | | 0.3336 | 3.0 | 1242 | 0.4255 | 0.8453 | 0.8411 |

Framework versions

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