robinsmits
/

Qwen1.5-7B-Dutch-Chat-Sft-Bf16

@@ -13,170 +13,69 @@ pipeline_tag: text-generation
 inference: false
 ---
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 ## Citation
 Thanks to the creators of Qwen1.5 for there great work!

 inference: false
 ---
+# Qwen1.5-7B-Dutch-Chat-Sft-Bf16
+## Model description
+This finetuned model is the merged version of the adapter model [robinsmits/Qwen1.5-7B-Dutch-Chat-Sft](https://huggingface.co/robinsmits/Qwen1.5-7B-Dutch-Chat-Sft).
+Finetuning was performed on the Dutch [BramVanroy/ultrachat_200k_dutch](https://huggingface.co/datasets/BramVanroy/ultrachat_200k_dutch) dataset.
+See [Qwen/Qwen1.5-7B-Chat](https://huggingface.co/Qwen/Qwen1.5-7B-Chat) for all information about the base model.
+## Intended uses & limitations
+As with all LLM's this model can also experience bias and hallucinations. Regardless of how you use this model always perform the necessary testing and validation.
+The used dataset does not allow commercial usage.
+## Training and evaluation data
+The training notebook is available at the following link: [Qwen1_5_7B_Dutch_Chat_SFT](https://github.com/RobinSmits/Dutch-LLMs/blob/main/Qwen1_5_7B_Dutch_Chat_SFT.ipynb)
+Training was performed with Google Colab PRO on a A100 - 40GB.
+As the amount of data was more than would fit within the maximum 24 hour session that Google Colab PRO allows I split the dataset in 2 equal parts. Training for each part lasted around 14 hours. In the second part I enabled 'resume_from_checkpoint' to continue the training.
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0003
+- train_batch_size: 2
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- training_steps: 1466
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.4493        | 0.2   | 146  | 1.4083          |
+| 1.3638        | 0.4   | 292  | 1.3213          |
+| 1.3146        | 0.6   | 438  | 1.2731          |
+| 1.2756        | 0.8   | 584  | 1.2400          |
+| 1.2533        | 1.0   | 730  | 1.2165          |
+| 1.2388        | 1.19  | 876  | 1.1998          |
+| 1.2246        | 1.39  | 1022 | 1.1882          |
+| 1.211         | 1.59  | 1168 | 1.1802          |
+| 1.204         | 1.79  | 1314 | 1.1763          |
+| 1.2041        | 1.99  | 1460 | 1.1756          |
+### Framework versions
+- PEFT 0.9.0
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2
 ## Citation
 Thanks to the creators of Qwen1.5 for there great work!