level_c_5_sentiment_tb_1

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level_c_5_sentiment_tb_1

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: 0.7422

accuracy

: 0.7042

f1

: 0.6576

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 | 0.8287 | 0.6667 | 0.6064 | | No log | 2.0 | 244 | 0.7801 | 0.6761 | 0.6130 | | No log | 3.0 | 366 | 0.7531 | 0.6620 | 0.6012 | | No log | 4.0 | 488 | 0.7665 | 0.6714 | 0.6070 | | 0.6839 | 5.0 | 610 | 0.7521 | 0.6714 | 0.6097 | | 0.6839 | 6.0 | 732 | 0.7441 | 0.6948 | 0.6335 | | 0.6839 | 7.0 | 854 | 0.7422 | 0.7042 | 0.6576 | | 0.6839 | 8.0 | 976 | 0.7579 | 0.7042 | 0.6583 | | 0.5158 | 9.0 | 1098 | 0.7714 | 0.6948 | 0.6595 |

Framework versions

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