metadata

base_model: gokuls/HBERTv1_48_L2_H768_A12
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: HBERTv1_48_L2_H768_A12_emotion
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: emotion
          type: emotion
          config: split
          split: validation
          args: split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.902

HBERTv1_48_L2_H768_A12_emotion

This model is a fine-tuned version of gokuls/HBERTv1_48_L2_H768_A12 on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.5001
Accuracy: 0.902

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: 33
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.652	1.0	250	0.3361	0.886
0.286	2.0	500	0.2842	0.8985
0.2136	3.0	750	0.3013	0.8895
0.1606	4.0	1000	0.3200	0.895
0.1234	5.0	1250	0.3292	0.8945
0.0937	6.0	1500	0.3903	0.8955
0.0682	7.0	1750	0.4032	0.8985
0.0471	8.0	2000	0.4627	0.9
0.0337	9.0	2250	0.4851	0.899
0.0269	10.0	2500	0.5001	0.902

Framework versions

Transformers 4.34.0
Pytorch 1.14.0a0+410ce96
Datasets 2.14.5
Tokenizers 0.14.0