Model save

README.md

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+---
+library_name: transformers
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: Llama3.1-8B-relu-stage-1-fineweb-edu-45B-4096
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.5.2`
+```yaml
+base_model: meta-llama/Llama-3.1-8B
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+tokenizer_use_fast: false
+resize_token_embeddings_to_32x: false
+
+flash_attention: true
+xformers_attention:
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: skymizer/Llama3.1-8B-base-tokenized-fineweb-edu-45B-4096
+    train_on_split: train
+    type: completion
+
+test_datasets:
+  - path: skymizer/Llama3.1-8B-base-tokenized-fineweb-edu-test-4K
+    split: test
+    type: completion
+
+is_preprocess: true
+skip_prepare_dataset: true
+
+dataset_prepared_path: /mnt/home/model-team/datasets/pretokenized/Llama3.1-8B-base-tokenized-fineweb-edu-45B-4096 
+
+hf_use_auth_token: true
+output_dir: /mnt/home/model-team/models/Llama3.1-8B-v0.1-relu-stage-1-fineweb-edu-45B-4096
+resume_from_checkpoint:
+auto_resume_from_checkpoints: true
+
+sequence_len: 4096
+sample_packing: true
+sample_packing_group_size: 100000
+sample_packing_bin_size: 200
+pad_to_sequence_len: true
+
+eval_sample_packing: false
+# eval_causal_lm_metrics: ["perplexity"]
+
+wandb_project: "sparse-tuning-cpt"
+wandb_entity:
+wandb_watch:
+wandb_name: "Llama3.1-8B-relu-stage-1-fineweb-edu-45B-4096"
+wandb_log_model:
+
+# global batch size = 2 * 8 * 8 GPUs * 8 Nodes * 4096 = 4M
+gradient_accumulation_steps: 8
+micro_batch_size: 2
+  # eval_batch_size: 2
+max_steps: 10000
+optimizer: adamw_torch
+learning_rate: 0.000015
+lr_scheduler: cosine
+cosine_min_lr_ratio: 1.0 
+weight_decay: 0.0
+adam_beta1: 0.9
+adam_beta2: 0.95
+adam_eps: 0.000001
+max_grad_norm: 1.0
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16:
+tf32: false
+
+hub_model_id: "skymizer/Llama3.1-8B-relu-stage-1-fineweb-edu-45B-4096"
+
+save_strategy: "steps"
+save_steps: 500
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+
+warmup_steps: 1
+eval_steps: 500
+eval_table_size:
+debug:
+deepspeed: /root/train/axolotl/deepspeed_configs/zero3_bf16.json
+fsdp:
+fsdp_config:
+seed: 42
+
+special_tokens:
+  pad_token: "<|end_of_text|>"
+
+```
+
+</details><br>
+
+# Llama3.1-8B-relu-stage-1-fineweb-edu-45B-4096
+
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9682
+
+## 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: 1.5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 64
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 1024
+- total_eval_batch_size: 128
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 2
+- training_steps: 10000
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| 12.2232       | 0.0001 | 1     | 12.1487         |
+| 2.2025        | 0.0424 | 500   | 2.2272          |
+| 2.1454        | 0.0848 | 1000  | 2.1515          |
+| 2.0991        | 0.1273 | 1500  | 2.1142          |
+| 2.0604        | 0.1697 | 2000  | 2.0894          |
+| 2.058         | 0.2121 | 2500  | 2.0711          |
+| 2.0582        | 0.2545 | 3000  | 2.0561          |
+| 2.0474        | 0.2969 | 3500  | 2.0442          |
+| 2.0268        | 0.3394 | 4000  | 2.0347          |
+| 2.0173        | 0.3818 | 4500  | 2.0256          |
+| 1.9941        | 0.4242 | 5000  | 2.0178          |
+| 2.0113        | 0.4666 | 5500  | 2.0106          |
+| 1.9949        | 0.5091 | 6000  | 2.0040          |
+| 2.0077        | 0.5515 | 6500  | 1.9984          |
+| 1.986         | 0.5939 | 7000  | 1.9935          |
+| 1.9902        | 0.6363 | 7500  | 1.9888          |
+| 1.9899        | 0.6787 | 8000  | 1.9841          |
+| 1.9729        | 0.7212 | 8500  | 1.9800          |
+| 1.971         | 0.7636 | 9000  | 1.9759          |
+| 1.9784        | 0.8060 | 9500  | 1.9718          |
+| 1.9553        | 0.8484 | 10000 | 1.9682          |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3