metadata

tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
model-index:
  - name: hbertv1-emotion_48_emb_compress
    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: 0.874

hbertv1-emotion_48_emb_compress

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48 on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.4493
Accuracy: 0.874

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
1.4218	1.0	250	1.1098	0.5885
0.9116	2.0	500	0.7865	0.743
0.5915	3.0	750	0.6149	0.805
0.4435	4.0	1000	0.4932	0.841
0.3626	5.0	1250	0.4634	0.855
0.3031	6.0	1500	0.4514	0.8545
0.2457	7.0	1750	0.4395	0.865
0.2039	8.0	2000	0.4368	0.861
0.1664	9.0	2250	0.4276	0.871
0.1402	10.0	2500	0.4493	0.874

Framework versions

Transformers 4.30.2
Pytorch 1.14.0a0+410ce96
Datasets 2.13.0
Tokenizers 0.13.3