metadata

license: apache-2.0
tags:
  - classification
  - generated_from_trainer
datasets:
  - poem_sentiment
metrics:
  - accuracy
base_model: bert-base-uncased
model-index:
  - name: clasificador-poem-sentiment
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: poem_sentiment
          type: poem_sentiment
          config: default
          split: test
          args: default
        metrics:
          - type: accuracy
            value: 0.8461538461538461
            name: Accuracy

clasificador-poem-sentiment

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

Loss: 0.7095
Accuracy: 0.8462

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	112	0.4617	0.875
No log	2.0	224	0.5310	0.8654
No log	3.0	336	0.7095	0.8462

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3