---
library_name: transformers
license: mit
base_model: CMU-AIRe/e3-1.7B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: e3-sft
  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. -->

# e3-sft

This model is a fine-tuned version of [CMU-AIRe/e3-1.7B](https://huggingface.co/CMU-AIRe/e3-1.7B) on the hardmath_sft_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6364

## 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-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_min_lr
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7025        | 4.0   | 16   | 0.7606          |
| 0.9105        | 8.0   | 32   | 0.7590          |
| 0.8193        | 12.0  | 48   | 0.7550          |
| 0.6939        | 16.0  | 64   | 0.7460          |
| 0.6623        | 20.0  | 80   | 0.7418          |
| 0.8112        | 24.0  | 96   | 0.7389          |
| 0.708         | 28.0  | 112  | 0.7154          |
| 0.6471        | 32.0  | 128  | 0.7097          |
| 0.9019        | 36.0  | 144  | 0.7050          |
| 0.7328        | 40.0  | 160  | 0.7007          |
| 0.8191        | 44.0  | 176  | 0.6938          |
| 0.6327        | 48.0  | 192  | 0.6752          |
| 0.6903        | 52.0  | 208  | 0.6604          |
| 0.7467        | 56.0  | 224  | 0.6533          |
| 0.7364        | 60.0  | 240  | 0.6489          |
| 0.7706        | 64.0  | 256  | 0.6460          |
| 0.7777        | 68.0  | 272  | 0.6441          |
| 0.6391        | 72.0  | 288  | 0.6419          |
| 0.648         | 76.0  | 304  | 0.6408          |
| 0.704         | 80.0  | 320  | 0.6398          |
| 0.6316        | 84.0  | 336  | 0.6387          |
| 0.6232        | 88.0  | 352  | 0.6380          |
| 0.6545        | 92.0  | 368  | 0.6372          |
| 0.7126        | 96.0  | 384  | 0.6364          |
| 0.6465        | 100.0 | 400  | 0.6364          |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.5.1
- Datasets 3.6.0
- Tokenizers 0.21.1