sentiment_analytics_bert_single

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: 0.3767

accuracy

: 0.8512

: 0.8470

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: 10

Training results

accuracy

| |:-------------:|:-----:|:----:|:---------------:|:------------:|:------:| | No log | 1.0 | 414 | 0.3767 | 0.8512 | 0.8470 | | 0.4461 | 2.0 | 828 | 0.3996 | 0.8244 | 0.8294 | | 0.3339 | 3.0 | 1242 | 0.4199 | 0.8302 | 0.8313 |

Framework versions

Transformers 4.45.2
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1

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Model size

66.4M params

Tensor type

F32

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