metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - emotion
metrics:
  - accuracy
base_model: distilbert-base-uncased
model-index:
  - name: sagemaker-distilbert-emotion-2
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: emotion
          type: emotion
          args: default
        metrics:
          - type: accuracy
            value: 0.9315
            name: Accuracy

sagemaker-distilbert-emotion-2

This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.1442
Accuracy: 0.9315

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: 32
eval_batch_size: 64
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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9316	1.0	500	0.2384	0.918
0.1849	2.0	1000	0.1599	0.9265
0.1047	3.0	1500	0.1442	0.9315

Framework versions

Transformers 4.12.3
Pytorch 1.9.1
Datasets 1.15.1
Tokenizers 0.10.3