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tadiecool29/STL-ethiollm-b-250K-sentiment
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metadata
library_name: transformers
license: mit
base_model: EthioNLP/EthioLLM-b-250K
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: STL-ethiollm-b-250K-sentiment
    results: []

STL-ethiollm-b-250K-sentiment

This model is a fine-tuned version of EthioNLP/EthioLLM-b-250K on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9272
  • Sentiment Precision: 0.6650
  • Sentiment Recall: 0.6514
  • F1: 0.6451
  • Sentiment Acc: 0.6484

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 300
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Sentiment Precision Sentiment Recall F1 Sentiment Acc
0.9908 1.0 377 0.8728 0.6072 0.6070 0.6071 0.6110
0.8654 2.0 754 0.8423 0.6625 0.6281 0.6123 0.6222
0.7344 3.0 1131 0.7865 0.6662 0.6595 0.6568 0.6584
0.6174 4.0 1508 0.7960 0.6592 0.6565 0.6532 0.6571
0.5512 5.0 1885 0.8839 0.6608 0.6438 0.6313 0.6434
0.4653 6.0 2262 0.9272 0.6650 0.6514 0.6451 0.6484

Framework versions

  • Transformers 5.16.1
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.23.1