pytorch tensorboard bert dataset:enoriega/odinsynth_dataset transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- enoriega/odinsynth_dataset
model-index:
- name: rule_learning_margin_test
  results: []
---

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# rule_learning_margin_test

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the enoriega/odinsynth_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4104

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2000
- total_train_batch_size: 8000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6468        | 0.32  | 20   | 0.6191          |
| 0.5185        | 0.64  | 40   | 0.5083          |
| 0.459         | 0.96  | 60   | 0.4521          |
| 0.4352        | 1.29  | 80   | 0.4192          |
| 0.4427        | 1.61  | 100  | 0.4199          |
| 0.4246        | 1.93  | 120  | 0.4131          |
| 0.4301        | 2.26  | 140  | 0.4104          |
| 0.428         | 2.58  | 160  | 0.4099          |
| 0.4161        | 2.9   | 180  | 0.4102          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.1
- Tokenizers 0.12.1
