metadata

license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
  - Language
  - image-Emotion
  - miniLM
  - PyTorch
  - Trainer
  - SequenceClassification
  - WeightedLoss
  - CrossEntropyLoss
  - F1Score
  - HuggingFaceHub
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - f1
model-index:
  - name: miniLM_finetuned_Emotion_2024_06_15
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: F1
            type: f1
            value: 0.927424135409491

miniLM_finetuned_Emotion_2024_06_15

This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.1881
F1: 0.9274

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: 64
eval_batch_size: 64
seed: 42
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	F1
1.1887	1.0	250	0.7672	0.7461
0.5641	2.0	500	0.3698	0.9058
0.3151	3.0	750	0.2783	0.9244
0.2074	4.0	1000	0.2417	0.9273
0.1586	5.0	1250	0.1749	0.9301
0.1287	6.0	1500	0.1945	0.9344
0.1112	7.0	1750	0.2054	0.9313
0.1031	8.0	2000	0.1677	0.9308
0.0819	9.0	2250	0.1862	0.9279
0.0743	10.0	2500	0.1881	0.9274

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1