---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- enoriega/odinsynth_sequence_dataset
metrics:
- accuracy
model-index:
- name: odinsynth_encoder_decoder_native_hf_test
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: enoriega/odinsynth_sequence_dataset synthetic_surface
      type: enoriega/odinsynth_sequence_dataset
      config: synthetic_surface
      split: validation
      args: synthetic_surface
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9332402379440391
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# odinsynth_encoder_decoder_native_hf_test

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the enoriega/odinsynth_sequence_dataset synthetic_surface 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