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secemp9
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TraceBack-12b

Text Generation
Transformers
Safetensors
mistral
Generated from Trainer
conversational
text-generation-inference
4-bit precision
bitsandbytes
Model card Files
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TraceBack-12b
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---
library_name: peft
license: apache-2.0
base_model: unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit
tags:
- generated_from_trainer
datasets:
- instruction_solution_to_thought_dataset.jsonl
model-index:
- name: outputs_solution_to_thought
  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: `0.7.0`
```yaml
# Base model configuration
base_model: unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit
load_in_4bit: true

# Dataset configuration
datasets:
  - path: instruction_solution_to_thought_dataset.jsonl
    type: chat_template

# Chat template
chat_template: chatml

# LoRA adapter configuration
adapter: lora
lora_r: 16
lora_alpha: 16
lora_dropout: 0
lora_target_modules:
  - q_proj
  - k_proj
  - v_proj
  - o_proj
  - gate_proj
  - up_proj
  - down_proj

# Training hyperparameters
max_seq_length: 128000
micro_batch_size: 2
gradient_accumulation_steps: 8
learning_rate: 3e-5
num_epochs: 2
warmup_steps: 100
optimizer: adamw_8bit
weight_decay: 0.01
lr_scheduler_type: cosine
max_grad_norm: 1.0
output_dir: ./outputs_solution_to_thought
seed: 3407
merge_lora: true
hf_upload: true
hf_repo: secemp9/TraceBack-12b
xformers_attention:
flash_attention: True
#lora_mlp_kernel: true
#lora_qkv_kernel: true
#lora_o_kernel: true
#fp16: true
#load_in_8bit: true  # Enable 8-bit loading for LoRA finetuning
bf16: true          # Enable BF16 mixed precision
# Multi-GPU training with DeepSpeed
deepspeed: deepspeed_configs/zero2.json

# Optional: Enable gradient checkpointing
gradient_checkpointing: true

```

</details><br>

# outputs_solution_to_thought

This model is a fine-tuned version of [unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407-bnb-4bit) on the instruction_solution_to_thought_dataset.jsonl dataset.

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 3407
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 2.0

### Training results



### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0