---
tags:
- generated_from_trainer
datasets:
- enoriega/odinsynth_dataset
model-index:
- name: rule_learning_margin_1mm_spanpred_attention
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# rule_learning_margin_1mm_spanpred_attention

This model is a fine-tuned version of [enoriega/rule_softmatching](https://huggingface.co/enoriega/rule_softmatching) on the enoriega/odinsynth_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3237
- Margin Accuracy: 0.8518

## 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 | Margin Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|
| 0.5768        | 0.16  | 20   | 0.5693          | 0.7577          |
| 0.4593        | 0.32  | 40   | 0.4338          | 0.8105          |
| 0.4219        | 0.48  | 60   | 0.3958          | 0.8218          |
| 0.3953        | 0.64  | 80   | 0.3809          | 0.8308          |
| 0.383         | 0.8   | 100  | 0.3684          | 0.8355          |
| 0.3781        | 0.96  | 120  | 0.3591          | 0.8396          |
| 0.354         | 1.12  | 140  | 0.3535          | 0.8420          |
| 0.3521        | 1.28  | 160  | 0.3491          | 0.8430          |
| 0.3533        | 1.44  | 180  | 0.3423          | 0.8466          |
| 0.344         | 1.6   | 200  | 0.3372          | 0.8472          |
| 0.3352        | 1.76  | 220  | 0.3345          | 0.8478          |
| 0.3318        | 1.92  | 240  | 0.3320          | 0.8487          |
| 0.3478        | 2.08  | 260  | 0.3286          | 0.8494          |
| 0.3329        | 2.24  | 280  | 0.3286          | 0.8505          |
| 0.3424        | 2.4   | 300  | 0.3262          | 0.8506          |
| 0.3463        | 2.56  | 320  | 0.3264          | 0.8512          |
| 0.3416        | 2.72  | 340  | 0.3247          | 0.8518          |
| 0.329         | 2.88  | 360  | 0.3247          | 0.8516          |


### Framework versions

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