metadata

tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
base_model: nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large
model-index:
  - name: MiniLMv2-L12-H384-emotion
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - type: accuracy
            value: 0.925
            name: Accuracy

MiniLMv2-L12-H384-emotion

This model is a fine-tuned version of nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.2069
Accuracy: 0.925

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: 3e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8745	1.0	1000	0.6673	0.81
0.3466	2.0	2000	0.2816	0.918
0.2201	3.0	3000	0.2367	0.9215
0.1761	4.0	4000	0.2069	0.925
0.1435	5.0	5000	0.2089	0.922
0.1454	6.0	6000	0.2168	0.923
0.1041	7.0	7000	0.2081	0.924
0.0953	8.0	8000	0.2133	0.9245

Framework versions

Transformers 4.12.3
Pytorch 1.9.1
Datasets 1.15.1
Tokenizers 0.10.3