---
library_name: transformers
license: mit
base_model: jhu-clsp/ettin-encoder-1b
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ettin-map-1b-singlefold
  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. -->

# ettin-map-1b-singlefold

This model is a fine-tuned version of [jhu-clsp/ettin-encoder-1b](https://huggingface.co/jhu-clsp/ettin-encoder-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2284
- Accuracy: 0.9137
- Map@3: 0.9559

## 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: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Map@3  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 4.65          | 0.5006 | 1000 | 0.3880          | 0.8524   | 0.9233 |
| 1.2856        | 1.0010 | 2000 | 0.3011          | 0.8845   | 0.9407 |
| 0.9807        | 1.5016 | 3000 | 0.2610          | 0.9029   | 0.9504 |
| 0.8878        | 2.0020 | 4000 | 0.2404          | 0.9085   | 0.9533 |
| 0.7293        | 2.5026 | 5000 | 0.2344          | 0.9118   | 0.9549 |
| 0.7067        | 3.0030 | 6000 | 0.2290          | 0.9140   | 0.9561 |
| 0.6482        | 3.5036 | 7000 | 0.2284          | 0.9137   | 0.9559 |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1