results_corrected_2_final

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

  • Loss: 0.6436

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: 7.412367436802549e-06
  • train_batch_size: 64
  • eval_batch_size: 16
  • seed: 30
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 6 0.6373
0.3049 2.0 12 0.6381
0.3049 3.0 18 0.6403
0.2832 4.0 24 0.6436

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Tokenizers 0.19.1
Downloads last month
6
Safetensors
Model size
167M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for callista6699/results_corrected_2_final

Finetuned
(24)
this model