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tiny-llama-lora

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tiny-llama-lora / README.md
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metadata
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: tiny-llama
    results: []

tiny-llama

This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-Chat-v1.0 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2265
  • Accuracy: 0.8327
  • Precision: 0.8301
  • Recall: 0.8327
  • Precision Macro: 0.7955
  • Recall Macro: 0.7536
  • Macro Fpr: 0.0148
  • Weighted Fpr: 0.0141
  • Weighted Specificity: 0.9765
  • Macro Specificity: 0.9873
  • Weighted Sensitivity: 0.8327
  • Macro Sensitivity: 0.7536
  • F1 Micro: 0.8327
  • F1 Macro: 0.7609
  • F1 Weighted: 0.8291

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-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall Precision Macro Recall Macro Macro Fpr Weighted Fpr Weighted Specificity Macro Specificity Weighted Sensitivity Macro Sensitivity F1 Micro F1 Macro F1 Weighted
1.0444 1.0 642 0.5968 0.8056 0.8050 0.8056 0.7122 0.6995 0.0175 0.0169 0.9730 0.9852 0.8056 0.6995 0.8056 0.6986 0.8014
0.4788 2.0 1284 0.6966 0.8195 0.8222 0.8195 0.8092 0.7825 0.0161 0.0155 0.9755 0.9863 0.8195 0.7825 0.8195 0.7849 0.8172
0.3354 3.0 1926 0.8046 0.8327 0.8276 0.8327 0.8058 0.7582 0.0148 0.0141 0.9758 0.9872 0.8327 0.7582 0.8327 0.7742 0.8282
0.0571 4.0 2569 1.1143 0.8265 0.8312 0.8265 0.7904 0.7763 0.0152 0.0148 0.9772 0.9869 0.8265 0.7763 0.8265 0.7690 0.8262
0.0187 5.0 3211 1.1104 0.8319 0.8316 0.8319 0.7745 0.7724 0.0149 0.0142 0.9770 0.9873 0.8319 0.7724 0.8319 0.7638 0.8303
0.0071 6.0 3853 1.1445 0.8242 0.8210 0.8242 0.7684 0.7384 0.0157 0.0150 0.9755 0.9866 0.8242 0.7384 0.8242 0.7451 0.8209
0.0002 7.0 4495 1.2032 0.8327 0.8302 0.8327 0.7985 0.7529 0.0148 0.0141 0.9765 0.9873 0.8327 0.7529 0.8327 0.7617 0.8293
0.0028 8.0 5138 1.1918 0.8257 0.8226 0.8257 0.7738 0.7493 0.0155 0.0149 0.9756 0.9868 0.8257 0.7493 0.8257 0.7552 0.8229
0.0 9.0 5780 1.2181 0.8311 0.8286 0.8311 0.7935 0.7522 0.0150 0.0143 0.9764 0.9872 0.8311 0.7522 0.8311 0.7592 0.8276
0.0018 10.0 6420 1.2265 0.8327 0.8301 0.8327 0.7955 0.7536 0.0148 0.0141 0.9765 0.9873 0.8327 0.7536 0.8327 0.7609 0.8291

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.1