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Dora-Smol

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llama
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Dora-Smol
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---
tags:
- generated_from_trainer
model-index:
- name: SmolLM-Ora
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml
base_model: /media/renfroe/llms/SmolLM-360M/

model_type: LlamaForCausalLM
tokenizer_type: GPT2Tokenizer
seed: 122887 
load_in_8bit: false
load_in_4bit: false
strict: false

max_steps: 0
resume_from_checkpoint: 
datasets:
  - path: /home/renfroe/Desktop/sqa_tiny-llama_dataset/Dynamic_Optimization_Methods_with_Applications_sqa_answers_only.json
    type:
      field_instruction: question
      field_output: answer
      format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
      no_input_format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
  - path: /home/renfroe/Dev/tinyllama-models/dataset/open_hermes_top_tech.json
    type: sharegpt
  - path:  /home/renfroe/Desktop/sqa_tiny-llama_dataset/hermes_prior_knowledge_question_expansion_with_answers.json
    type:
      field_instruction: question
      field_output: answer
      format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
      no_input_format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
  - path:  /home/renfroe/Desktop/sqa_tiny-llama_dataset/hermes_prior_knowledge_question_expansion_with_answers.json
    type:
      field_instruction: question
      field_output: answer
      format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
      no_input_format: "<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
  - path:  /home/renfroe/Desktop/sqa_tiny-llama_dataset/or-farm_sharegpt.json
    type: sharegpt
  


dataset_prepared_path:
val_set_size: 0.2
output_dir: ./SmolLM-Ora
auto_resume_from_checkpoints: false

sequence_len: 2048
sample_packing: true
chat_template: chatml

wandb_project: SmolLM-Ora
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 10
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: linear
weight_decay: 0.0000001
learning_rate: 0.0001
lr_scheduler_kwargs:
  #  num_cycles: 3 

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

eval_sample_packing: False

warmup_steps: 50
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 4
debug:
deepspeed:

fsdp:
fsdp_config:
special_tokens:
  bos_token: "<|endoftext|>"
  eos_token: "<|endoftext|>"
  pad_token: "<|endoftext|>"
```

</details><br>

# SmolLM-Ora

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8298

## 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: 10
- eval_batch_size: 10
- seed: 122887
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0131        | 0.01  | 1    | 1.0419          |
| 0.9727        | 0.25  | 27   | 0.9962          |
| 0.953         | 0.5   | 54   | 0.9076          |
| 0.8494        | 0.75  | 81   | 0.8792          |
| 0.9297        | 1.0   | 108  | 0.8632          |
| 0.8801        | 1.22  | 135  | 0.8527          |
| 0.8133        | 1.47  | 162  | 0.8459          |
| 0.8342        | 1.72  | 189  | 0.8410          |
| 0.8973        | 1.97  | 216  | 0.8376          |
| 0.7731        | 2.19  | 243  | 0.8350          |
| 0.8207        | 2.44  | 270  | 0.8332          |
| 0.7963        | 2.69  | 297  | 0.8318          |
| 0.81          | 2.94  | 324  | 0.8309          |
| 0.8351        | 3.18  | 351  | 0.8302          |
| 0.8104        | 3.43  | 378  | 0.8299          |
| 0.9019        | 3.68  | 405  | 0.8298          |
| 0.7828        | 3.93  | 432  | 0.8298          |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.0