---
tags:
- generated_from_trainer
model-index:
- name: home/suika/bin/axolotl/OUT-perscengen/
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# home/suika/bin/axolotl/OUT-perscengen/

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8290

## 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: 0.00025
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.992         | 0.06  | 15   | 1.8884          |
| 1.8026        | 0.12  | 30   | 1.8655          |
| 1.7713        | 0.19  | 45   | 1.8539          |
| 1.7145        | 0.25  | 60   | 1.8502          |
| 1.6686        | 0.31  | 75   | 1.8507          |
| 1.8409        | 0.37  | 90   | 1.8469          |
| 1.7741        | 0.44  | 105  | 1.8434          |
| 1.7384        | 0.5   | 120  | 1.8407          |
| 1.7562        | 0.56  | 135  | 1.8390          |
| 1.7392        | 0.62  | 150  | 1.8373          |
| 1.8735        | 0.68  | 165  | 1.8381          |
| 1.8406        | 0.75  | 180  | 1.8377          |
| 1.6602        | 0.81  | 195  | 1.8350          |
| 1.7803        | 0.87  | 210  | 1.8341          |
| 1.7212        | 0.93  | 225  | 1.8329          |
| 1.8126        | 1.0   | 240  | 1.8330          |
| 1.8776        | 1.06  | 255  | 1.8314          |
| 1.7892        | 1.12  | 270  | 1.8328          |
| 1.7029        | 1.18  | 285  | 1.8338          |
| 1.7094        | 1.24  | 300  | 1.8322          |
| 1.7921        | 1.31  | 315  | 1.8310          |
| 1.8309        | 1.37  | 330  | 1.8316          |
| 1.7373        | 1.43  | 345  | 1.8309          |
| 1.7873        | 1.49  | 360  | 1.8313          |
| 1.7151        | 1.56  | 375  | 1.8306          |
| 1.7529        | 1.62  | 390  | 1.8300          |
| 1.7516        | 1.68  | 405  | 1.8293          |
| 1.7704        | 1.74  | 420  | 1.8294          |
| 1.6351        | 1.8   | 435  | 1.8290          |
| 1.6186        | 1.87  | 450  | 1.8291          |
| 1.7086        | 1.93  | 465  | 1.8295          |
| 1.6595        | 1.99  | 480  | 1.8290          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0