Upload README.md

README.md

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+---
+library_name: transformers
+base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
+tags:
+- generated_from_trainer
+model-index:
+- name: outputs/out
+  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: `0.4.1`
+```yaml
+base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
+    type: sharegpt
+    conversation: chatml
+  - path: NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered
+    type: sharegpt
+    conversation: chatml
+  - path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
+    type: sharegpt
+    conversation: chatml
+  - path: NewEden/Gryphe-Sonnet-3.5-35k-Subset
+    type: sharegpt
+    conversation: chatml
+  - path: jeiku/Nitral_Medical_Dialog_Fixed
+    type: sharegpt
+    conversation: chatml
+
+chat_template: chatml
+
+val_set_size: 0.01
+output_dir: ./outputs/out
+
+adapter:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+
+sequence_len: 8192
+# sequence_len: 32768
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len: true
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+
+wandb_project: New8B
+wandb_entity:
+wandb_watch:
+wandb_name: New8B
+wandb_log_model:
+
+gradient_accumulation_steps: 32
+micro_batch_size: 1
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.00001
+weight_decay: 0.05
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_ratio: 0.1
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 2
+
+debug:
+deepspeed:
+fsdp:
+fsdp_config:
+
+special_tokens:
+  pad_token: <pad>
+
+
+```
+
+</details><br>
+
+# outputs/out
+
+This model is a fine-tuned version of [Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML](https://huggingface.co/Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0138
+
+## 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: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 64
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 23
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.4041        | 0.0084 | 1    | 1.5854          |
+| 1.0445        | 0.2534 | 30   | 1.1313          |
+| 0.9479        | 0.5069 | 60   | 1.0488          |
+| 0.9697        | 0.7603 | 90   | 1.0288          |
+| 0.9126        | 1.0090 | 120  | 1.0193          |
+| 0.9006        | 1.2621 | 150  | 1.0156          |
+| 0.9038        | 1.5153 | 180  | 1.0140          |
+| 0.9095        | 1.7685 | 210  | 1.0138          |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1