level_c_huge_sentiment_tb_0

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.9157

accuracy

: 0.5915

f1

: 0.5720

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: 5e-06
• 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 | 122 | 4.2726 | 0.4554 | 0.4479 | | No log | 2.0 | 244 | 3.6147 | 0.4789 | 0.4755 | | No log | 3.0 | 366 | 3.2739 | 0.4977 | 0.4940 | | No log | 4.0 | 488 | 3.1773 | 0.5164 | 0.5061 | | 3.7586 | 5.0 | 610 | 2.9913 | 0.5305 | 0.5201 | | 3.7586 | 6.0 | 732 | 2.6793 | 0.5211 | 0.5105 | | 3.7586 | 7.0 | 854 | 2.6357 | 0.5681 | 0.5527 | | 3.7586 | 8.0 | 976 | 2.5609 | 0.5446 | 0.5219 | | 2.4153 | 9.0 | 1098 | 2.5325 | 0.5352 | 0.5142 | | 2.4153 | 10.0 | 1220 | 2.2139 | 0.5446 | 0.5396 | | 2.4153 | 11.0 | 1342 | 2.2626 | 0.5493 | 0.5331 | | 2.4153 | 12.0 | 1464 | 2.1830 | 0.5493 | 0.5302 | | 1.5224 | 13.0 | 1586 | 2.0396 | 0.5352 | 0.5329 | | 1.5224 | 14.0 | 1708 | 2.0469 | 0.5728 | 0.5591 | | 1.5224 | 15.0 | 1830 | 1.9968 | 0.5587 | 0.5475 | | 1.5224 | 16.0 | 1952 | 1.9542 | 0.5728 | 0.5617 | | 0.9782 | 17.0 | 2074 | 1.9774 | 0.5728 | 0.5581 | | 0.9782 | 18.0 | 2196 | 1.9157 | 0.5915 | 0.5720 | | 0.9782 | 19.0 | 2318 | 1.9316 | 0.5915 | 0.5715 | | 0.9782 | 20.0 | 2440 | 1.9433 | 0.5728 | 0.5523 |

Framework versions

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