---
license: cc-by-nc-4.0
inference: false
datasets:
- BramVanroy/alpaca-cleaned-dutch
base_model: DAMO-NLP-MT/polylm-1.7b
tags:
- generated_from_trainer
- alpaca
- Transformers
- PolyLM
- text-generation-inference
model-index:
- name: polylm_1.7b_ft_alpaca_clean_dutch
  results: []
language:
- nl
library_name: peft
pipeline_tag: text-generation
---

<!-- 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. -->

# polylm_1.7b_ft_alpaca_clean_dutch

This model is a fine-tuned version of [DAMO-NLP-MT/polylm-1.7b](https://huggingface.co/DAMO-NLP-MT/polylm-1.7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8174

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 64
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0693        | 0.16  | 128  | 2.0915          |
| 2.0029        | 0.33  | 256  | 2.0195          |
| 2.0006        | 0.49  | 384  | 1.9779          |
| 1.933         | 0.66  | 512  | 1.9409          |
| 1.9532        | 0.82  | 640  | 1.9217          |
| 1.8959        | 0.99  | 768  | 1.8978          |
| 1.8237        | 1.15  | 896  | 1.8838          |
| 1.8218        | 1.32  | 1024 | 1.8693          |
| 1.8072        | 1.48  | 1152 | 1.8521          |
| 1.8103        | 1.65  | 1280 | 1.8395          |
| 1.8275        | 1.81  | 1408 | 1.8266          |
| 1.7902        | 1.98  | 1536 | 1.8174          |


### Framework versions

- PEFT 0.4.0
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- PEFT 0.4.0