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---
library_name: peft
license: apache-2.0
base_model: unsloth/SmolLM2-360M-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: ef2c8c76-79b1-448e-ab76-1fade52ab206
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
adapter: lora
base_model: unsloth/SmolLM2-360M-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 892ffe9842e626bd_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/892ffe9842e626bd_train_data.json
type:
field_instruction: premise
field_output: hypothesis
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: dixedus/ef2c8c76-79b1-448e-ab76-1fade52ab206
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 200
micro_batch_size: 8
mlflow_experiment_name: /tmp/892ffe9842e626bd_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: 686ea06b-435c-4c19-932a-671d02350bf4
wandb_project: Gradients-On-Eight
wandb_run: your_name
wandb_runid: 686ea06b-435c-4c19-932a-671d02350bf4
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# ef2c8c76-79b1-448e-ab76-1fade52ab206
This model is a fine-tuned version of [unsloth/SmolLM2-360M-Instruct](https://huggingface.co/unsloth/SmolLM2-360M-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1006
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 200
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log | 0.0055 | 1 | 3.8842 |
| 3.315 | 0.0938 | 17 | 3.4181 |
| 2.8794 | 0.1876 | 34 | 2.8203 |
| 2.512 | 0.2814 | 51 | 2.4239 |
| 2.1655 | 0.3752 | 68 | 2.2579 |
| 2.3072 | 0.4690 | 85 | 2.1796 |
| 1.9292 | 0.5628 | 102 | 2.1434 |
| 1.9992 | 0.6566 | 119 | 2.1214 |
| 1.9635 | 0.7503 | 136 | 2.1131 |
| 2.1538 | 0.8441 | 153 | 2.1072 |
| 2.2758 | 0.9379 | 170 | 2.1024 |
| 2.0053 | 1.0317 | 187 | 2.1006 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1