metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - poem_sentiment
metrics:
  - accuracy
  - f1
model-index:
  - name: distilbert-base-uncased-finetuned-rating-poem
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: poem_sentiment
          type: poem_sentiment
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8761904761904762
          - name: F1
            type: f1
            value: 0.8765098002671388

distilbert-base-uncased-finetuned-rating-poem

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

Loss: 1.1902
Accuracy: 0.8762
F1: 0.8765

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: 2e-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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.0599	0.45	50	1.0247	0.8571	0.8611
0.1257	0.89	100	1.1237	0.8571	0.8500
0.032	1.34	150	1.1346	0.8667	0.8567
0.0012	1.79	200	1.2181	0.8381	0.8373
0.0954	2.23	250	1.0423	0.8762	0.8667
0.0323	2.68	300	1.0560	0.8667	0.8715
0.0128	3.12	350	1.1156	0.8857	0.8809
0.0269	3.57	400	1.1702	0.8762	0.8681
0.0172	4.02	450	1.1968	0.8667	0.8678
0.0004	4.46	500	1.1906	0.8762	0.8765
0.0117	4.91	550	1.1902	0.8762	0.8765

Framework versions

Transformers 4.32.1
Pytorch 2.2.2
Datasets 2.12.0
Tokenizers 0.13.2