---
license: apache-2.0
base_model: allenai/OLMo-1B
tags:
- generated_from_trainer
model-index:
- name: O0430HMA16
  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. -->

# O0430HMA16

This model is a fine-tuned version of [allenai/OLMo-1B](https://huggingface.co/allenai/OLMo-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1386

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5715        | 0.09  | 10   | 0.2837          |
| 0.1807        | 0.18  | 20   | 0.1554          |
| 0.1515        | 0.27  | 30   | 0.1672          |
| 0.1573        | 0.36  | 40   | 0.1535          |
| 0.1517        | 0.45  | 50   | 0.1504          |
| 0.1521        | 0.54  | 60   | 0.1490          |
| 0.1513        | 0.63  | 70   | 0.1472          |
| 0.1494        | 0.73  | 80   | 0.1574          |
| 0.1484        | 0.82  | 90   | 0.1490          |
| 0.149         | 0.91  | 100  | 0.1494          |
| 0.1512        | 1.0   | 110  | 0.1499          |
| 0.1463        | 1.09  | 120  | 0.1482          |
| 0.1462        | 1.18  | 130  | 0.1522          |
| 0.1484        | 1.27  | 140  | 0.1487          |
| 0.1499        | 1.36  | 150  | 0.1501          |
| 0.1463        | 1.45  | 160  | 0.1478          |
| 0.146         | 1.54  | 170  | 0.1477          |
| 0.1472        | 1.63  | 180  | 0.1472          |
| 0.1461        | 1.72  | 190  | 0.1490          |
| 0.1443        | 1.81  | 200  | 0.1497          |
| 0.1494        | 1.9   | 210  | 0.1503          |
| 0.1456        | 1.99  | 220  | 0.1472          |
| 0.1429        | 2.08  | 230  | 0.1446          |
| 0.1383        | 2.18  | 240  | 0.1445          |
| 0.1401        | 2.27  | 250  | 0.1450          |
| 0.141         | 2.36  | 260  | 0.1459          |
| 0.1398        | 2.45  | 270  | 0.1428          |
| 0.1341        | 2.54  | 280  | 0.1389          |
| 0.1345        | 2.63  | 290  | 0.1411          |
| 0.1347        | 2.72  | 300  | 0.1395          |
| 0.1335        | 2.81  | 310  | 0.1387          |
| 0.1321        | 2.9   | 320  | 0.1387          |
| 0.1375        | 2.99  | 330  | 0.1386          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1