---
library_name: transformers
license: mit
base_model: jhu-clsp/ettin-encoder-1b
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ettin_refine_balanced
  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_refine_balanced

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: 0.2446
- Accuracy: 0.9132
- Map@3: 0.9555

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Map@3  |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.343         | 1.7398 | 1000 | 0.2446          | 0.9132   | 0.9555 |


### Framework versions

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