---
library_name: peft
license: other
base_model: facebook/opt-1.3b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: cc4a3486-a710-49ea-8182-a30d05a62e39
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# cc4a3486-a710-49ea-8182-a30d05a62e39

This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0536

## 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: 0.000201
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 50
- training_steps: 400

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0028 | 1    | 1.0241          |
| 0.52          | 0.1379 | 50   | 0.1036          |
| 0.5061        | 0.2759 | 100  | 0.1104          |
| 0.1155        | 0.4138 | 150  | 0.0543          |
| 0.3057        | 0.5517 | 200  | 0.0534          |
| 0.0765        | 0.6897 | 250  | 0.0592          |
| 0.3329        | 0.8276 | 300  | 0.0546          |
| 0.0479        | 0.9655 | 350  | 0.0536          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1