peft tensorboard safetensors generated_from_trainer base_model:vlsp-2023-vllm/hoa-1b4 license:bigscience-bloom-rail-1.0 region:us
---
license: bigscience-bloom-rail-1.0
library_name: peft
tags:
- generated_from_trainer
base_model: vlsp-2023-vllm/hoa-1b4
model-index:
- name: hoa-1b4_model_kaggle_test
  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. -->

# hoa-1b4_model_kaggle_test

This model is a fine-tuned version of [vlsp-2023-vllm/hoa-1b4](https://huggingface.co/vlsp-2023-vllm/hoa-1b4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0088

## 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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 7    | 3.2766          |
| No log        | 2.0   | 14   | 2.8527          |
| No log        | 3.0   | 21   | 2.6111          |
| No log        | 4.0   | 28   | 2.3834          |
| No log        | 5.0   | 35   | 2.1930          |
| No log        | 6.0   | 42   | 2.0336          |
| No log        | 7.0   | 49   | 1.8676          |
| No log        | 8.0   | 56   | 1.7066          |
| No log        | 9.0   | 63   | 1.5550          |
| No log        | 10.0  | 70   | 1.4148          |
| No log        | 11.0  | 77   | 1.2909          |
| No log        | 12.0  | 84   | 1.1698          |
| No log        | 13.0  | 91   | 1.0494          |
| No log        | 14.0  | 98   | 0.9417          |
| No log        | 15.0  | 105  | 0.8308          |
| No log        | 16.0  | 112  | 0.7236          |
| No log        | 17.0  | 119  | 0.6239          |
| No log        | 18.0  | 126  | 0.5360          |
| No log        | 19.0  | 133  | 0.4547          |
| No log        | 20.0  | 140  | 0.3911          |
| No log        | 21.0  | 147  | 0.3288          |
| No log        | 22.0  | 154  | 0.2807          |
| No log        | 23.0  | 161  | 0.2396          |
| No log        | 24.0  | 168  | 0.2013          |
| No log        | 25.0  | 175  | 0.1764          |
| No log        | 26.0  | 182  | 0.1483          |
| No log        | 27.0  | 189  | 0.1240          |
| No log        | 28.0  | 196  | 0.1128          |
| No log        | 29.0  | 203  | 0.0983          |
| No log        | 30.0  | 210  | 0.0868          |
| No log        | 31.0  | 217  | 0.0775          |
| No log        | 32.0  | 224  | 0.0722          |
| No log        | 33.0  | 231  | 0.0613          |
| No log        | 34.0  | 238  | 0.0570          |
| No log        | 35.0  | 245  | 0.0495          |
| No log        | 36.0  | 252  | 0.0441          |
| No log        | 37.0  | 259  | 0.0409          |
| No log        | 38.0  | 266  | 0.0360          |
| No log        | 39.0  | 273  | 0.0314          |
| No log        | 40.0  | 280  | 0.0296          |
| No log        | 41.0  | 287  | 0.0250          |
| No log        | 42.0  | 294  | 0.0231          |
| No log        | 43.0  | 301  | 0.0241          |
| No log        | 44.0  | 308  | 0.0196          |
| No log        | 45.0  | 315  | 0.0183          |
| No log        | 46.0  | 322  | 0.0176          |
| No log        | 47.0  | 329  | 0.0173          |
| No log        | 48.0  | 336  | 0.0143          |
| No log        | 49.0  | 343  | 0.0145          |
| No log        | 50.0  | 350  | 0.0138          |
| No log        | 51.0  | 357  | 0.0131          |
| No log        | 52.0  | 364  | 0.0138          |
| No log        | 53.0  | 371  | 0.0142          |
| No log        | 54.0  | 378  | 0.0137          |
| No log        | 55.0  | 385  | 0.0119          |
| No log        | 56.0  | 392  | 0.0123          |
| No log        | 57.0  | 399  | 0.0122          |
| No log        | 58.0  | 406  | 0.0112          |
| No log        | 59.0  | 413  | 0.0114          |
| No log        | 60.0  | 420  | 0.0112          |
| No log        | 61.0  | 427  | 0.0108          |
| No log        | 62.0  | 434  | 0.0105          |
| No log        | 63.0  | 441  | 0.0120          |
| No log        | 64.0  | 448  | 0.0110          |
| No log        | 65.0  | 455  | 0.0115          |
| No log        | 66.0  | 462  | 0.0102          |
| No log        | 67.0  | 469  | 0.0104          |
| No log        | 68.0  | 476  | 0.0113          |
| No log        | 69.0  | 483  | 0.0098          |
| No log        | 70.0  | 490  | 0.0101          |
| No log        | 71.0  | 497  | 0.0101          |
| 0.4941        | 72.0  | 504  | 0.0094          |
| 0.4941        | 73.0  | 511  | 0.0097          |
| 0.4941        | 74.0  | 518  | 0.0095          |
| 0.4941        | 75.0  | 525  | 0.0101          |
| 0.4941        | 76.0  | 532  | 0.0095          |
| 0.4941        | 77.0  | 539  | 0.0100          |
| 0.4941        | 78.0  | 546  | 0.0092          |
| 0.4941        | 79.0  | 553  | 0.0094          |
| 0.4941        | 80.0  | 560  | 0.0095          |
| 0.4941        | 81.0  | 567  | 0.0094          |
| 0.4941        | 82.0  | 574  | 0.0093          |
| 0.4941        | 83.0  | 581  | 0.0093          |
| 0.4941        | 84.0  | 588  | 0.0094          |
| 0.4941        | 85.0  | 595  | 0.0092          |
| 0.4941        | 86.0  | 602  | 0.0089          |
| 0.4941        | 87.0  | 609  | 0.0090          |
| 0.4941        | 88.0  | 616  | 0.0090          |
| 0.4941        | 89.0  | 623  | 0.0089          |
| 0.4941        | 90.0  | 630  | 0.0088          |
| 0.4941        | 91.0  | 637  | 0.0089          |
| 0.4941        | 92.0  | 644  | 0.0088          |
| 0.4941        | 93.0  | 651  | 0.0088          |
| 0.4941        | 94.0  | 658  | 0.0088          |
| 0.4941        | 95.0  | 665  | 0.0088          |
| 0.4941        | 96.0  | 672  | 0.0088          |
| 0.4941        | 97.0  | 679  | 0.0088          |
| 0.4941        | 98.0  | 686  | 0.0088          |
| 0.4941        | 99.0  | 693  | 0.0088          |
| 0.4941        | 100.0 | 700  | 0.0088          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2