zodiache/unaligned

1---2license: llama33library_name: peft4tags:5- trl6- sft7- generated_from_trainer8base_model: meta-llama/Meta-Llama-3-8B-Instruct9model-index:10- name: unaligned11  results: []12---13 14<!-- This model card has been generated automatically according to the information the Trainer had access to. You15should probably proofread and complete it, then remove this comment. -->16 17# unaligned18 19This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.20It achieves the following results on the evaluation set:21- Loss: 0.070922 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 0.000241- train_batch_size: 842- eval_batch_size: 843- seed: 4244- gradient_accumulation_steps: 845- total_train_batch_size: 6446- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0847- lr_scheduler_type: linear48- lr_scheduler_warmup_steps: 10049- training_steps: 204850 51### Training results52 53| Training Loss | Epoch  | Step | Validation Loss |54|:-------------:|:------:|:----:|:---------------:|55| 0.1154        | 0.1110 | 100  | 0.1172          |56| 0.092         | 0.2220 | 200  | 0.1028          |57| 0.0462        | 0.3330 | 300  | 0.0992          |58| 0.0482        | 0.4440 | 400  | 0.0755          |59| 0.043         | 0.5550 | 500  | 0.0794          |60| 0.0476        | 0.6660 | 600  | 0.0628          |61| 0.0482        | 0.7770 | 700  | 0.0821          |62| 0.0484        | 0.8880 | 800  | 0.0691          |63| 0.0448        | 0.9990 | 900  | 0.0829          |64| 0.0214        | 1.1100 | 1000 | 0.0720          |65| 0.0439        | 1.2210 | 1100 | 0.0635          |66| 0.0364        | 1.3320 | 1200 | 0.0713          |67| 0.0497        | 1.4430 | 1300 | 0.0669          |68| 0.0455        | 1.5540 | 1400 | 0.0672          |69| 0.0614        | 1.6650 | 1500 | 0.0805          |70| 0.0416        | 1.7761 | 1600 | 0.0669          |71| 0.0367        | 1.8871 | 1700 | 0.0716          |72| 0.0578        | 1.9981 | 1800 | 0.0684          |73| 0.0358        | 2.1091 | 1900 | 0.0705          |74| 0.0326        | 2.2201 | 2000 | 0.0709          |75 76 77### Framework versions78 79- PEFT 0.11.180- Transformers 4.41.181- Pytorch 2.3.0+cu12182- Datasets 2.19.183- Tokenizers 0.19.1