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--- |
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license: llama3 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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model-index: |
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- name: mathvi/output_model2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: /workspace/axolotl/mathvi/input_output_meta_llama_3_8b_instruct-00000-of-00001.parquet |
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type: input_output |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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eval_sample_packing: false |
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output_dir: mathvi/output_model2 |
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sequence_len: 4096 |
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sample_packing: false |
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pad_to_sequence_len: false |
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adapter: lora |
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lora_model_dir: |
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lora_r: 64 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 32 |
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micro_batch_size: 4 |
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num_epochs: 3 |
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optimizer: paged_adamw_32bit |
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lr_scheduler: cosine |
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learning_rate: 2e-4 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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s2_attention: |
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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 10 |
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evals_per_epoch: 10 |
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eval_table_size: |
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eval_max_new_tokens: 512 |
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saves_per_epoch: 2 |
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save_total_limit: 20 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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# mathvi/output_model2 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3327 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.0442 | 0.0190 | 1 | 2.0734 | |
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| 1.449 | 0.1137 | 6 | 1.2774 | |
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| 0.8548 | 0.2275 | 12 | 0.9006 | |
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| 0.8561 | 0.3412 | 18 | 0.7924 | |
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| 0.744 | 0.4550 | 24 | 0.7176 | |
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| 0.6752 | 0.5687 | 30 | 0.6603 | |
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| 0.5908 | 0.6825 | 36 | 0.6117 | |
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| 0.5229 | 0.7962 | 42 | 0.5702 | |
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| 0.558 | 0.9100 | 48 | 0.5281 | |
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| 0.4343 | 1.0237 | 54 | 0.4752 | |
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| 0.4039 | 1.1374 | 60 | 0.4152 | |
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| 0.3744 | 1.2512 | 66 | 0.4225 | |
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| 0.3313 | 1.3649 | 72 | 0.3852 | |
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| 0.374 | 1.4787 | 78 | 0.3740 | |
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| 0.3246 | 1.5924 | 84 | 0.3657 | |
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| 0.3392 | 1.7062 | 90 | 0.3591 | |
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| 0.3309 | 1.8199 | 96 | 0.3505 | |
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| 0.3621 | 1.9336 | 102 | 0.3437 | |
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| 0.2819 | 2.0474 | 108 | 0.3416 | |
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| 0.2672 | 2.1611 | 114 | 0.3414 | |
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| 0.2284 | 2.2749 | 120 | 0.3375 | |
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| 0.2836 | 2.3886 | 126 | 0.3353 | |
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| 0.2504 | 2.5024 | 132 | 0.3337 | |
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| 0.2696 | 2.6161 | 138 | 0.3328 | |
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| 0.2775 | 2.7299 | 144 | 0.3327 | |
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| 0.2554 | 2.8436 | 150 | 0.3325 | |
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| 0.2551 | 2.9573 | 156 | 0.3327 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
