metadata

base_model: gokuls/HBERTv1_48_L10_H128_A2
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: HBERTv1_48_L10_H128_A2_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: 0.8865

HBERTv1_48_L10_H128_A2_emotion

This model is a fine-tuned version of gokuls/HBERTv1_48_L10_H128_A2 on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.3362
Accuracy: 0.8865

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
1.4132	1.0	250	1.1283	0.5875
0.9519	2.0	500	0.7405	0.757
0.6375	3.0	750	0.5533	0.8295
0.4709	4.0	1000	0.4480	0.8625
0.3802	5.0	1250	0.4056	0.8665
0.3246	6.0	1500	0.3581	0.877
0.2718	7.0	1750	0.3616	0.877
0.2422	8.0	2000	0.3427	0.8805
0.2157	9.0	2250	0.3452	0.8845
0.2026	10.0	2500	0.3362	0.8865

Framework versions

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