metadata

tags:
  - generated_from_trainer
datasets:
  - odinsynth_sequence_dataset
metrics:
  - accuracy
model-index:
  - name: odinsynth_encoder_decoder_native_hf_test
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: odinsynth_sequence_dataset
          type: odinsynth_sequence_dataset
          config: synthetic_surface
          split: validation
          args: synthetic_surface
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9332272780290561

odinsynth_encoder_decoder_native_hf_test

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

Loss: 0.0533
Accuracy: 0.9332

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: 3
eval_batch_size: 3
seed: 42
gradient_accumulation_steps: 200
total_train_batch_size: 600
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.5753	0.67	60	6.1666	0.0150
2.5262	1.34	120	2.1713	0.9345
0.2343	2.01	180	0.1787	0.9346
0.0713	2.68	240	0.0686	0.9330
0.0631	3.35	300	0.0621	0.9334
0.0603	4.02	360	0.0594	0.9332
0.0589	4.69	420	0.0583	0.9334
0.0579	5.36	480	0.0572	0.9336
0.0575	6.03	540	0.0566	0.9333
0.0561	6.69	600	0.0562	0.9333
0.0559	7.36	660	0.0559	0.9332
0.0551	8.03	720	0.0556	0.9332
0.0548	8.7	780	0.0552	0.9333
0.0546	9.37	840	0.0550	0.9333
0.0539	10.04	900	0.0547	0.9331
0.0546	10.71	960	0.0544	0.9332
0.0538	11.38	1020	0.0543	0.9335
0.0534	12.05	1080	0.0540	0.9333
0.0532	12.72	1140	0.0539	0.9334
0.0525	13.39	1200	0.0538	0.9334
0.0526	14.06	1260	0.0538	0.9331
0.0527	14.73	1320	0.0536	0.9331
0.0529	15.4	1380	0.0536	0.9331
0.0526	16.07	1440	0.0535	0.9331
0.0524	16.74	1500	0.0534	0.9333
0.0516	17.41	1560	0.0534	0.9331
0.0527	18.08	1620	0.0534	0.9332
0.0521	18.74	1680	0.0533	0.9332
0.0519	19.41	1740	0.0533	0.9332

Framework versions

Transformers 4.27.4
Pytorch 2.0.0
Datasets 2.11.0
Tokenizers 0.11.0