transformers tensorboard safetensors llama text-generation alignment-handbook trl sft generated_from_trainer conversational dataset:HuggingFaceH4/ultrachat_200k base_model:KnutJaegersberg/Qwen-1_8B-Llamafied license:other autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: other
base_model: KnutJaegersberg/Qwen-1_8B-Llamafied
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: qwen_1_8B_llamafied
  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. -->

# qwen_1_8B_llamafied

This model is a fine-tuned version of [KnutJaegersberg/Qwen-1_8B-Llamafied](https://huggingface.co/KnutJaegersberg/Qwen-1_8B-Llamafied) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2486

## 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: 2e-05
- train_batch_size: 12
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 120
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3881        | 0.1   | 100  | 1.3937          |
| 1.3499        | 0.2   | 200  | 1.3372          |
| 1.3138        | 0.3   | 300  | 1.3168          |
| 1.3152        | 0.4   | 400  | 1.3045          |
| 1.2897        | 0.5   | 500  | 1.2954          |
| 1.28          | 0.6   | 600  | 1.2882          |
| 1.2669        | 0.7   | 700  | 1.2820          |
| 1.2591        | 0.8   | 800  | 1.2768          |
| 1.2447        | 0.9   | 900  | 1.2721          |
| 1.2867        | 1.0   | 1000 | 1.2680          |
| 1.1918        | 1.1   | 1100 | 1.2684          |
| 1.2002        | 1.2   | 1200 | 1.2660          |
| 1.1943        | 1.3   | 1300 | 1.2633          |
| 1.199         | 1.4   | 1400 | 1.2607          |
| 1.1887        | 1.5   | 1500 | 1.2581          |
| 1.1987        | 1.6   | 1600 | 1.2556          |
| 1.1954        | 1.7   | 1700 | 1.2534          |
| 1.1869        | 1.8   | 1800 | 1.2511          |
| 1.1744        | 1.9   | 1900 | 1.2492          |
| 1.1718        | 2.0   | 2000 | 1.2486          |
| 1.1456        | 2.1   | 2100 | 1.2532          |
| 1.1204        | 2.2   | 2200 | 1.2529          |
| 1.1347        | 2.3   | 2300 | 1.2519          |
| 1.1312        | 2.4   | 2400 | 1.2513          |
| 1.1229        | 2.5   | 2500 | 1.2508          |
| 1.1287        | 2.6   | 2600 | 1.2500          |
| 1.1252        | 2.7   | 2700 | 1.2500          |
| 1.139         | 2.8   | 2800 | 1.2498          |
| 1.1282        | 2.9   | 2900 | 1.2497          |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
