---
library_name: peft
license: apache-2.0
base_model: unsloth/SmolLM2-135M
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 7c127b20-70fd-4530-a059-d012d4b84589
  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
adapter: lora
auto_find_batch_size: true
base_model: unsloth/SmolLM2-135M
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - eeb2c3714f5569ba_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/eeb2c3714f5569ba_train_data.json
  type:
    field_instruction: rxn_smiles
    field_output: prod_smiles
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: /workspace/axolotl/configs/deepspeed_stage2.json
eval_max_new_tokens: 128
eval_sample_packing: false
eval_steps: 10
eval_table_size: null
flash_attention: true
fp16: false
gpu_memory_limit: 80GiB
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: PhoenixB/7c127b20-70fd-4530-a059-d012d4b84589
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 2e-4
liger_fused_linear_cross_entropy: true
liger_glu_activation: true
liger_layer_norm: true
liger_rms_norm: true
liger_rope: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 5
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/eeb2c3714f5569ba_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
plugins:
- axolotl.integrations.liger.LigerPlugin
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 8192
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: ad992704-c1f0-47d6-b2a6-7c02c6f3452f
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ad992704-c1f0-47d6-b2a6-7c02c6f3452f
warmup_steps: 10
weight_decay: 0.0

```

</details><br>

# 7c127b20-70fd-4530-a059-d012d4b84589

This model is a fine-tuned version of [unsloth/SmolLM2-135M](https://huggingface.co/unsloth/SmolLM2-135M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8485

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 10
- training_steps: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0003 | 1    | 3.8583          |
| 3.667         | 0.0034 | 10   | 3.6824          |
| 3.1653        | 0.0069 | 20   | 2.9001          |
| 2.5476        | 0.0103 | 30   | 2.4427          |
| 2.3111        | 0.0137 | 40   | 2.1900          |
| 2.0557        | 0.0172 | 50   | 2.0402          |
| 1.9822        | 0.0206 | 60   | 1.9592          |
| 1.8217        | 0.0241 | 70   | 1.8934          |
| 1.9404        | 0.0275 | 80   | 1.8680          |
| 1.8577        | 0.0309 | 90   | 1.8518          |
| 1.8435        | 0.0344 | 100  | 1.8485          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3