| | --- |
| | library_name: transformers |
| | license: other |
| | base_model: meta-llama/Meta-Llama-3-8B-Instruct |
| | tags: |
| | - llama-factory |
| | - full |
| | - generated_from_trainer |
| | model-index: |
| | - name: no_explain |
| | 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. --> |
| |
|
| | # no_explain |
| | |
| | This 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 chess_explain_noexplain_00, the chess_explain_noexplain_01, the chess_explain_noexplain_02, the chess_explain_noexplain_03, the chess_explain_noexplain_04, the chess_explain_noexplain_05, the chess_explain_noexplain_06, the chess_explain_noexplain_07, the chess_explain_noexplain_08, the chess_explain_noexplain_09, the chess_explain_noexplain_10, the chess_explain_noexplain_11, the chess_explain_noexplain_12, the chess_explain_noexplain_13 and the chess_explain_noexplain_14 datasets. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0932 |
| |
|
| | ## 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: 5e-06 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 8 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 1024 |
| | - total_eval_batch_size: 512 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10.0 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 0.0429 | 0.8010 | 1000 | 0.0422 | |
| | | 0.0329 | 1.6015 | 2000 | 0.0336 | |
| | | 0.0275 | 2.4021 | 3000 | 0.0297 | |
| | | 0.0202 | 3.2026 | 4000 | 0.0292 | |
| | | 0.0194 | 4.0032 | 5000 | 0.0294 | |
| | | 0.0119 | 4.8042 | 6000 | 0.0311 | |
| | | 0.0048 | 5.6047 | 7000 | 0.0439 | |
| | | 0.0013 | 6.4053 | 8000 | 0.0538 | |
| | | 0.0004 | 7.2058 | 9000 | 0.0670 | |
| | | 0.0003 | 8.0064 | 10000 | 0.0698 | |
| | | 0.0 | 8.8074 | 11000 | 0.0894 | |
| | | 0.0 | 9.6079 | 12000 | 0.0931 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.48.2 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 2.21.0 |
| | - Tokenizers 0.21.0 |
| | |
