pytorch opt text-generation transformers generated_from_trainer license:other model-index
---
license: other
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: opt-model
  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. -->

# opt-model

This model is a fine-tuned version of [facebook/opt-13b](https://huggingface.co/facebook/opt-13b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3965
- Accuracy: 0.5020

## 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: 24
- eval_batch_size: 24
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 72
- total_eval_batch_size: 72
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.6363        | 1.0   | 3    | 3.2090          | 0.4082   |
| 2.8168        | 2.0   | 6    | 2.4805          | 0.4874   |
| 2.3529        | 3.0   | 9    | 2.4219          | 0.4915   |
| 2.1842        | 4.0   | 12   | 2.4023          | 0.4991   |
| 2.0765        | 5.0   | 15   | 2.3965          | 0.5020   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
